Randeng-Deltalm-362M-En-Zh
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IDEA-CCNL
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Quick Summary
使用封神框架基于 Detalm base 进行finetune ，搜集的中英数据集（共3千万条）以及 iwslt的中英平行数据（20万），得到 英-> 中方向的翻译模型 Using the Fengshen-LM framework and finetuning based on detalm , get a tra...
Code Examples
下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。下游效果 Performancepythontransformers
# Need to download modeling_deltalm.py from Fengshenbang-LM github repo in advance,
# or you can download modeling_deltalm.py use wget https://huggingface.co/IDEA-CCNL/Randeng-Deltalm-362M-En-Zn/resolve/main/modeling_deltalm.py
# Strongly recommend you git clone the Fengshenbang-LM repo:
# 1. git clone https://github.com/IDEA-CCNL/Fengshenbang-LM
# 2. cd Fengshenbang-LM/fengshen/
from models.deltalm.modeling_deltalm import DeltalmForConditionalGeneration
from transformers import AutoTokenizer
model = DeltalmForConditionalGeneration.from_pretrained("IDEA-CCNL/Randeng-Deltalm-362M-En-Zn")
tokenizer = AutoTokenizer.from_pretrained("microsoft/infoxlm-base")
text = "In summer, especially, you'll need to watch out for mosquitoes if you decide to hike through the rainforest."
inputs = tokenizer(text, max_length=512, return_tensors="pt")
generate_ids = model.generate(inputs["input_ids"], max_length=512)
tokenizer.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# model Output:
# 如果你决定徒步穿越热带雨林,你需要小心蚊子,尤其是在夏天。Deploy This Model
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