marin-8b-instruct

137
24
1 language
llama
by
marin-community
Language Model
OTHER
8B params
New
137 downloads
Early-stage
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Edge AI:
Mobile
Laptop
Server
18GB+ RAM
Mobile
Laptop
Server
Quick Summary

AI model with specialized capabilities.

Device Compatibility

Mobile
4-6GB RAM
Laptop
16GB RAM
Server
GPU
Minimum Recommended
8GB+ RAM

Code Examples

Inferencepythontransformers
from transformers import AutoModelForCausalLM, AutoTokenizer
marin = AutoModelForCausalLM.from_pretrained("marin-community/marin-8b-base")
tokenizer = AutoTokenizer.from_pretrained("marin-community/marin-8b-base")
message = ["The Marin wind is"]
inputs = tokenizer(message, return_tensors='pt', return_token_type_ids=False)
response = marin.generate(**inputs, max_new_tokens=100, do_sample=True, top_k=50, top_p=0.95)
print(tokenizer.batch_decode(response, skip_special_tokens=True)[0])
Inferencepythontransformers
from transformers import AutoModelForCausalLM, AutoTokenizer
marin = AutoModelForCausalLM.from_pretrained("marin-community/marin-8b-base")
tokenizer = AutoTokenizer.from_pretrained("marin-community/marin-8b-base")
message = ["The Marin wind is"]
inputs = tokenizer(message, return_tensors='pt', return_token_type_ids=False)
response = marin.generate(**inputs, max_new_tokens=100, do_sample=True, top_k=50, top_p=0.95)
print(tokenizer.batch_decode(response, skip_special_tokens=True)[0])
Inferencepythontransformers
from transformers import AutoModelForCausalLM, AutoTokenizer
marin = AutoModelForCausalLM.from_pretrained("marin-community/marin-8b-base")
tokenizer = AutoTokenizer.from_pretrained("marin-community/marin-8b-base")
message = ["The Marin wind is"]
inputs = tokenizer(message, return_tensors='pt', return_token_type_ids=False)
response = marin.generate(**inputs, max_new_tokens=100, do_sample=True, top_k=50, top_p=0.95)
print(tokenizer.batch_decode(response, skip_special_tokens=True)[0])
Inferencepythontransformers
from transformers import AutoModelForCausalLM, AutoTokenizer
marin = AutoModelForCausalLM.from_pretrained("marin-community/marin-8b-base")
tokenizer = AutoTokenizer.from_pretrained("marin-community/marin-8b-base")
message = ["The Marin wind is"]
inputs = tokenizer(message, return_tensors='pt', return_token_type_ids=False)
response = marin.generate(**inputs, max_new_tokens=100, do_sample=True, top_k=50, top_p=0.95)
print(tokenizer.batch_decode(response, skip_special_tokens=True)[0])
Inferencepythontransformers
from transformers import AutoModelForCausalLM, AutoTokenizer
marin = AutoModelForCausalLM.from_pretrained("marin-community/marin-8b-base")
tokenizer = AutoTokenizer.from_pretrained("marin-community/marin-8b-base")
message = ["The Marin wind is"]
inputs = tokenizer(message, return_tensors='pt', return_token_type_ids=False)
response = marin.generate(**inputs, max_new_tokens=100, do_sample=True, top_k=50, top_p=0.95)
print(tokenizer.batch_decode(response, skip_special_tokens=True)[0])
Inferencepythontransformers
from transformers import AutoModelForCausalLM, AutoTokenizer
marin = AutoModelForCausalLM.from_pretrained("marin-community/marin-8b-base")
tokenizer = AutoTokenizer.from_pretrained("marin-community/marin-8b-base")
message = ["The Marin wind is"]
inputs = tokenizer(message, return_tensors='pt', return_token_type_ids=False)
response = marin.generate(**inputs, max_new_tokens=100, do_sample=True, top_k=50, top_p=0.95)
print(tokenizer.batch_decode(response, skip_special_tokens=True)[0])
Inferencepythontransformers
from transformers import AutoModelForCausalLM, AutoTokenizer
marin = AutoModelForCausalLM.from_pretrained("marin-community/marin-8b-base")
tokenizer = AutoTokenizer.from_pretrained("marin-community/marin-8b-base")
message = ["The Marin wind is"]
inputs = tokenizer(message, return_tensors='pt', return_token_type_ids=False)
response = marin.generate(**inputs, max_new_tokens=100, do_sample=True, top_k=50, top_p=0.95)
print(tokenizer.batch_decode(response, skip_special_tokens=True)[0])
Inferencepythontransformers
from transformers import AutoModelForCausalLM, AutoTokenizer
marin = AutoModelForCausalLM.from_pretrained("marin-community/marin-8b-base")
tokenizer = AutoTokenizer.from_pretrained("marin-community/marin-8b-base")
message = ["The Marin wind is"]
inputs = tokenizer(message, return_tensors='pt', return_token_type_ids=False)
response = marin.generate(**inputs, max_new_tokens=100, do_sample=True, top_k=50, top_p=0.95)
print(tokenizer.batch_decode(response, skip_special_tokens=True)[0])
Inferencepythontransformers
from transformers import AutoModelForCausalLM, AutoTokenizer
marin = AutoModelForCausalLM.from_pretrained("marin-community/marin-8b-base")
tokenizer = AutoTokenizer.from_pretrained("marin-community/marin-8b-base")
message = ["The Marin wind is"]
inputs = tokenizer(message, return_tensors='pt', return_token_type_ids=False)
response = marin.generate(**inputs, max_new_tokens=100, do_sample=True, top_k=50, top_p=0.95)
print(tokenizer.batch_decode(response, skip_special_tokens=True)[0])
Inferencepythontransformers
from transformers import AutoModelForCausalLM, AutoTokenizer
marin = AutoModelForCausalLM.from_pretrained("marin-community/marin-8b-base")
tokenizer = AutoTokenizer.from_pretrained("marin-community/marin-8b-base")
message = ["The Marin wind is"]
inputs = tokenizer(message, return_tensors='pt', return_token_type_ids=False)
response = marin.generate(**inputs, max_new_tokens=100, do_sample=True, top_k=50, top_p=0.95)
print(tokenizer.batch_decode(response, skip_special_tokens=True)[0])
Inferencepythontransformers
from transformers import AutoModelForCausalLM, AutoTokenizer
marin = AutoModelForCausalLM.from_pretrained("marin-community/marin-8b-base")
tokenizer = AutoTokenizer.from_pretrained("marin-community/marin-8b-base")
message = ["The Marin wind is"]
inputs = tokenizer(message, return_tensors='pt', return_token_type_ids=False)
response = marin.generate(**inputs, max_new_tokens=100, do_sample=True, top_k=50, top_p=0.95)
print(tokenizer.batch_decode(response, skip_special_tokens=True)[0])
Inferencepythontransformers
from transformers import AutoModelForCausalLM, AutoTokenizer
marin = AutoModelForCausalLM.from_pretrained("marin-community/marin-8b-base")
tokenizer = AutoTokenizer.from_pretrained("marin-community/marin-8b-base")
message = ["The Marin wind is"]
inputs = tokenizer(message, return_tensors='pt', return_token_type_ids=False)
response = marin.generate(**inputs, max_new_tokens=100, do_sample=True, top_k=50, top_p=0.95)
print(tokenizer.batch_decode(response, skip_special_tokens=True)[0])
Inferencepythontransformers
from transformers import AutoModelForCausalLM, AutoTokenizer
marin = AutoModelForCausalLM.from_pretrained("marin-community/marin-8b-base")
tokenizer = AutoTokenizer.from_pretrained("marin-community/marin-8b-base")
message = ["The Marin wind is"]
inputs = tokenizer(message, return_tensors='pt', return_token_type_ids=False)
response = marin.generate(**inputs, max_new_tokens=100, do_sample=True, top_k=50, top_p=0.95)
print(tokenizer.batch_decode(response, skip_special_tokens=True)[0])
Inferencepythontransformers
from transformers import AutoModelForCausalLM, AutoTokenizer
marin = AutoModelForCausalLM.from_pretrained("marin-community/marin-8b-base")
tokenizer = AutoTokenizer.from_pretrained("marin-community/marin-8b-base")
message = ["The Marin wind is"]
inputs = tokenizer(message, return_tensors='pt', return_token_type_ids=False)
response = marin.generate(**inputs, max_new_tokens=100, do_sample=True, top_k=50, top_p=0.95)
print(tokenizer.batch_decode(response, skip_special_tokens=True)[0])
Inferencepythontransformers
from transformers import AutoModelForCausalLM, AutoTokenizer
marin = AutoModelForCausalLM.from_pretrained("marin-community/marin-8b-base")
tokenizer = AutoTokenizer.from_pretrained("marin-community/marin-8b-base")
message = ["The Marin wind is"]
inputs = tokenizer(message, return_tensors='pt', return_token_type_ids=False)
response = marin.generate(**inputs, max_new_tokens=100, do_sample=True, top_k=50, top_p=0.95)
print(tokenizer.batch_decode(response, skip_special_tokens=True)[0])
Inferencepythontransformers
from transformers import AutoModelForCausalLM, AutoTokenizer
marin = AutoModelForCausalLM.from_pretrained("marin-community/marin-8b-base")
tokenizer = AutoTokenizer.from_pretrained("marin-community/marin-8b-base")
message = ["The Marin wind is"]
inputs = tokenizer(message, return_tensors='pt', return_token_type_ids=False)
response = marin.generate(**inputs, max_new_tokens=100, do_sample=True, top_k=50, top_p=0.95)
print(tokenizer.batch_decode(response, skip_special_tokens=True)[0])
Inferencepythontransformers
from transformers import AutoModelForCausalLM, AutoTokenizer
marin = AutoModelForCausalLM.from_pretrained("marin-community/marin-8b-base")
tokenizer = AutoTokenizer.from_pretrained("marin-community/marin-8b-base")
message = ["The Marin wind is"]
inputs = tokenizer(message, return_tensors='pt', return_token_type_ids=False)
response = marin.generate(**inputs, max_new_tokens=100, do_sample=True, top_k=50, top_p=0.95)
print(tokenizer.batch_decode(response, skip_special_tokens=True)[0])
Inferencepythontransformers
from transformers import AutoModelForCausalLM, AutoTokenizer
marin = AutoModelForCausalLM.from_pretrained("marin-community/marin-8b-base")
tokenizer = AutoTokenizer.from_pretrained("marin-community/marin-8b-base")
message = ["The Marin wind is"]
inputs = tokenizer(message, return_tensors='pt', return_token_type_ids=False)
response = marin.generate(**inputs, max_new_tokens=100, do_sample=True, top_k=50, top_p=0.95)
print(tokenizer.batch_decode(response, skip_special_tokens=True)[0])
Inferencepythontransformers
from transformers import AutoModelForCausalLM, AutoTokenizer
marin = AutoModelForCausalLM.from_pretrained("marin-community/marin-8b-base")
tokenizer = AutoTokenizer.from_pretrained("marin-community/marin-8b-base")
message = ["The Marin wind is"]
inputs = tokenizer(message, return_tensors='pt', return_token_type_ids=False)
response = marin.generate(**inputs, max_new_tokens=100, do_sample=True, top_k=50, top_p=0.95)
print(tokenizer.batch_decode(response, skip_special_tokens=True)[0])
Inferencepythontransformers
from transformers import AutoModelForCausalLM, AutoTokenizer
marin = AutoModelForCausalLM.from_pretrained("marin-community/marin-8b-base")
tokenizer = AutoTokenizer.from_pretrained("marin-community/marin-8b-base")
message = ["The Marin wind is"]
inputs = tokenizer(message, return_tensors='pt', return_token_type_ids=False)
response = marin.generate(**inputs, max_new_tokens=100, do_sample=True, top_k=50, top_p=0.95)
print(tokenizer.batch_decode(response, skip_special_tokens=True)[0])
Inferencepythontransformers
from transformers import AutoModelForCausalLM, AutoTokenizer
marin = AutoModelForCausalLM.from_pretrained("marin-community/marin-8b-base")
tokenizer = AutoTokenizer.from_pretrained("marin-community/marin-8b-base")
message = ["The Marin wind is"]
inputs = tokenizer(message, return_tensors='pt', return_token_type_ids=False)
response = marin.generate(**inputs, max_new_tokens=100, do_sample=True, top_k=50, top_p=0.95)
print(tokenizer.batch_decode(response, skip_special_tokens=True)[0])
Inferencepythontransformers
from transformers import AutoModelForCausalLM, AutoTokenizer
marin = AutoModelForCausalLM.from_pretrained("marin-community/marin-8b-base")
tokenizer = AutoTokenizer.from_pretrained("marin-community/marin-8b-base")
message = ["The Marin wind is"]
inputs = tokenizer(message, return_tensors='pt', return_token_type_ids=False)
response = marin.generate(**inputs, max_new_tokens=100, do_sample=True, top_k=50, top_p=0.95)
print(tokenizer.batch_decode(response, skip_special_tokens=True)[0])
Inferencepythontransformers
from transformers import AutoModelForCausalLM, AutoTokenizer
marin = AutoModelForCausalLM.from_pretrained("marin-community/marin-8b-base")
tokenizer = AutoTokenizer.from_pretrained("marin-community/marin-8b-base")
message = ["The Marin wind is"]
inputs = tokenizer(message, return_tensors='pt', return_token_type_ids=False)
response = marin.generate(**inputs, max_new_tokens=100, do_sample=True, top_k=50, top_p=0.95)
print(tokenizer.batch_decode(response, skip_special_tokens=True)[0])
Inferencepythontransformers
from transformers import AutoModelForCausalLM, AutoTokenizer
marin = AutoModelForCausalLM.from_pretrained("marin-community/marin-8b-base")
tokenizer = AutoTokenizer.from_pretrained("marin-community/marin-8b-base")
message = ["The Marin wind is"]
inputs = tokenizer(message, return_tensors='pt', return_token_type_ids=False)
response = marin.generate(**inputs, max_new_tokens=100, do_sample=True, top_k=50, top_p=0.95)
print(tokenizer.batch_decode(response, skip_special_tokens=True)[0])
Inferencepythontransformers
from transformers import AutoModelForCausalLM, AutoTokenizer
marin = AutoModelForCausalLM.from_pretrained("marin-community/marin-8b-base")
tokenizer = AutoTokenizer.from_pretrained("marin-community/marin-8b-base")
message = ["The Marin wind is"]
inputs = tokenizer(message, return_tensors='pt', return_token_type_ids=False)
response = marin.generate(**inputs, max_new_tokens=100, do_sample=True, top_k=50, top_p=0.95)
print(tokenizer.batch_decode(response, skip_special_tokens=True)[0])
Inferencepythontransformers
from transformers import AutoModelForCausalLM, AutoTokenizer
marin = AutoModelForCausalLM.from_pretrained("marin-community/marin-8b-base")
tokenizer = AutoTokenizer.from_pretrained("marin-community/marin-8b-base")
message = ["The Marin wind is"]
inputs = tokenizer(message, return_tensors='pt', return_token_type_ids=False)
response = marin.generate(**inputs, max_new_tokens=100, do_sample=True, top_k=50, top_p=0.95)
print(tokenizer.batch_decode(response, skip_special_tokens=True)[0])
Inferencepythontransformers
from transformers import AutoModelForCausalLM, AutoTokenizer
marin = AutoModelForCausalLM.from_pretrained("marin-community/marin-8b-base")
tokenizer = AutoTokenizer.from_pretrained("marin-community/marin-8b-base")
message = ["The Marin wind is"]
inputs = tokenizer(message, return_tensors='pt', return_token_type_ids=False)
response = marin.generate(**inputs, max_new_tokens=100, do_sample=True, top_k=50, top_p=0.95)
print(tokenizer.batch_decode(response, skip_special_tokens=True)[0])
Inferencepythontransformers
from transformers import AutoModelForCausalLM, AutoTokenizer
marin = AutoModelForCausalLM.from_pretrained("marin-community/marin-8b-base")
tokenizer = AutoTokenizer.from_pretrained("marin-community/marin-8b-base")
message = ["The Marin wind is"]
inputs = tokenizer(message, return_tensors='pt', return_token_type_ids=False)
response = marin.generate(**inputs, max_new_tokens=100, do_sample=True, top_k=50, top_p=0.95)
print(tokenizer.batch_decode(response, skip_special_tokens=True)[0])
Inferencepythontransformers
from transformers import AutoModelForCausalLM, AutoTokenizer
marin = AutoModelForCausalLM.from_pretrained("marin-community/marin-8b-base")
tokenizer = AutoTokenizer.from_pretrained("marin-community/marin-8b-base")
message = ["The Marin wind is"]
inputs = tokenizer(message, return_tensors='pt', return_token_type_ids=False)
response = marin.generate(**inputs, max_new_tokens=100, do_sample=True, top_k=50, top_p=0.95)
print(tokenizer.batch_decode(response, skip_special_tokens=True)[0])
Inferencepythontransformers
from transformers import AutoModelForCausalLM, AutoTokenizer
marin = AutoModelForCausalLM.from_pretrained("marin-community/marin-8b-base")
tokenizer = AutoTokenizer.from_pretrained("marin-community/marin-8b-base")
message = ["The Marin wind is"]
inputs = tokenizer(message, return_tensors='pt', return_token_type_ids=False)
response = marin.generate(**inputs, max_new_tokens=100, do_sample=True, top_k=50, top_p=0.95)
print(tokenizer.batch_decode(response, skip_special_tokens=True)[0])
Inferencepythontransformers
from transformers import AutoModelForCausalLM, AutoTokenizer
marin = AutoModelForCausalLM.from_pretrained("marin-community/marin-8b-base")
tokenizer = AutoTokenizer.from_pretrained("marin-community/marin-8b-base")
message = ["The Marin wind is"]
inputs = tokenizer(message, return_tensors='pt', return_token_type_ids=False)
response = marin.generate(**inputs, max_new_tokens=100, do_sample=True, top_k=50, top_p=0.95)
print(tokenizer.batch_decode(response, skip_special_tokens=True)[0])
Inferencepythontransformers
from transformers import AutoModelForCausalLM, AutoTokenizer
marin = AutoModelForCausalLM.from_pretrained("marin-community/marin-8b-base")
tokenizer = AutoTokenizer.from_pretrained("marin-community/marin-8b-base")
message = ["The Marin wind is"]
inputs = tokenizer(message, return_tensors='pt', return_token_type_ids=False)
response = marin.generate(**inputs, max_new_tokens=100, do_sample=True, top_k=50, top_p=0.95)
print(tokenizer.batch_decode(response, skip_special_tokens=True)[0])
Inferencepythontransformers
from transformers import AutoModelForCausalLM, AutoTokenizer
marin = AutoModelForCausalLM.from_pretrained("marin-community/marin-8b-base")
tokenizer = AutoTokenizer.from_pretrained("marin-community/marin-8b-base")
message = ["The Marin wind is"]
inputs = tokenizer(message, return_tensors='pt', return_token_type_ids=False)
response = marin.generate(**inputs, max_new_tokens=100, do_sample=True, top_k=50, top_p=0.95)
print(tokenizer.batch_decode(response, skip_special_tokens=True)[0])
Inferencepythontransformers
from transformers import AutoModelForCausalLM, AutoTokenizer
marin = AutoModelForCausalLM.from_pretrained("marin-community/marin-8b-base")
tokenizer = AutoTokenizer.from_pretrained("marin-community/marin-8b-base")
message = ["The Marin wind is"]
inputs = tokenizer(message, return_tensors='pt', return_token_type_ids=False)
response = marin.generate(**inputs, max_new_tokens=100, do_sample=True, top_k=50, top_p=0.95)
print(tokenizer.batch_decode(response, skip_special_tokens=True)[0])
Inferencepythontransformers
from transformers import AutoModelForCausalLM, AutoTokenizer
marin = AutoModelForCausalLM.from_pretrained("marin-community/marin-8b-base")
tokenizer = AutoTokenizer.from_pretrained("marin-community/marin-8b-base")
message = ["The Marin wind is"]
inputs = tokenizer(message, return_tensors='pt', return_token_type_ids=False)
response = marin.generate(**inputs, max_new_tokens=100, do_sample=True, top_k=50, top_p=0.95)
print(tokenizer.batch_decode(response, skip_special_tokens=True)[0])
Inferencepythontransformers
from transformers import AutoModelForCausalLM, AutoTokenizer
marin = AutoModelForCausalLM.from_pretrained("marin-community/marin-8b-base")
tokenizer = AutoTokenizer.from_pretrained("marin-community/marin-8b-base")
message = ["The Marin wind is"]
inputs = tokenizer(message, return_tensors='pt', return_token_type_ids=False)
response = marin.generate(**inputs, max_new_tokens=100, do_sample=True, top_k=50, top_p=0.95)
print(tokenizer.batch_decode(response, skip_special_tokens=True)[0])
Inferencepythontransformers
from transformers import AutoModelForCausalLM, AutoTokenizer
marin = AutoModelForCausalLM.from_pretrained("marin-community/marin-8b-base")
tokenizer = AutoTokenizer.from_pretrained("marin-community/marin-8b-base")
message = ["The Marin wind is"]
inputs = tokenizer(message, return_tensors='pt', return_token_type_ids=False)
response = marin.generate(**inputs, max_new_tokens=100, do_sample=True, top_k=50, top_p=0.95)
print(tokenizer.batch_decode(response, skip_special_tokens=True)[0])
Inferencepythontransformers
from transformers import AutoModelForCausalLM, AutoTokenizer
marin = AutoModelForCausalLM.from_pretrained("marin-community/marin-8b-base")
tokenizer = AutoTokenizer.from_pretrained("marin-community/marin-8b-base")
message = ["The Marin wind is"]
inputs = tokenizer(message, return_tensors='pt', return_token_type_ids=False)
response = marin.generate(**inputs, max_new_tokens=100, do_sample=True, top_k=50, top_p=0.95)
print(tokenizer.batch_decode(response, skip_special_tokens=True)[0])
Inferencepythontransformers
from transformers import AutoModelForCausalLM, AutoTokenizer
marin = AutoModelForCausalLM.from_pretrained("marin-community/marin-8b-base")
tokenizer = AutoTokenizer.from_pretrained("marin-community/marin-8b-base")
message = ["The Marin wind is"]
inputs = tokenizer(message, return_tensors='pt', return_token_type_ids=False)
response = marin.generate(**inputs, max_new_tokens=100, do_sample=True, top_k=50, top_p=0.95)
print(tokenizer.batch_decode(response, skip_special_tokens=True)[0])
Inferencepythontransformers
from transformers import AutoModelForCausalLM, AutoTokenizer
marin = AutoModelForCausalLM.from_pretrained("marin-community/marin-8b-base")
tokenizer = AutoTokenizer.from_pretrained("marin-community/marin-8b-base")
message = ["The Marin wind is"]
inputs = tokenizer(message, return_tensors='pt', return_token_type_ids=False)
response = marin.generate(**inputs, max_new_tokens=100, do_sample=True, top_k=50, top_p=0.95)
print(tokenizer.batch_decode(response, skip_special_tokens=True)[0])
Inferencepythontransformers
from transformers import AutoModelForCausalLM, AutoTokenizer
marin = AutoModelForCausalLM.from_pretrained("marin-community/marin-8b-base")
tokenizer = AutoTokenizer.from_pretrained("marin-community/marin-8b-base")
message = ["The Marin wind is"]
inputs = tokenizer(message, return_tensors='pt', return_token_type_ids=False)
response = marin.generate(**inputs, max_new_tokens=100, do_sample=True, top_k=50, top_p=0.95)
print(tokenizer.batch_decode(response, skip_special_tokens=True)[0])
Inferencepythontransformers
from transformers import AutoModelForCausalLM, AutoTokenizer
marin = AutoModelForCausalLM.from_pretrained("marin-community/marin-8b-base")
tokenizer = AutoTokenizer.from_pretrained("marin-community/marin-8b-base")
message = ["The Marin wind is"]
inputs = tokenizer(message, return_tensors='pt', return_token_type_ids=False)
response = marin.generate(**inputs, max_new_tokens=100, do_sample=True, top_k=50, top_p=0.95)
print(tokenizer.batch_decode(response, skip_special_tokens=True)[0])
Inferencepythontransformers
from transformers import AutoModelForCausalLM, AutoTokenizer
marin = AutoModelForCausalLM.from_pretrained("marin-community/marin-8b-base")
tokenizer = AutoTokenizer.from_pretrained("marin-community/marin-8b-base")
message = ["The Marin wind is"]
inputs = tokenizer(message, return_tensors='pt', return_token_type_ids=False)
response = marin.generate(**inputs, max_new_tokens=100, do_sample=True, top_k=50, top_p=0.95)
print(tokenizer.batch_decode(response, skip_special_tokens=True)[0])
Inferencepythontransformers
from transformers import AutoModelForCausalLM, AutoTokenizer
marin = AutoModelForCausalLM.from_pretrained("marin-community/marin-8b-base")
tokenizer = AutoTokenizer.from_pretrained("marin-community/marin-8b-base")
message = ["The Marin wind is"]
inputs = tokenizer(message, return_tensors='pt', return_token_type_ids=False)
response = marin.generate(**inputs, max_new_tokens=100, do_sample=True, top_k=50, top_p=0.95)
print(tokenizer.batch_decode(response, skip_special_tokens=True)[0])
Inferencepythontransformers
from transformers import AutoModelForCausalLM, AutoTokenizer
marin = AutoModelForCausalLM.from_pretrained("marin-community/marin-8b-base")
tokenizer = AutoTokenizer.from_pretrained("marin-community/marin-8b-base")
message = ["The Marin wind is"]
inputs = tokenizer(message, return_tensors='pt', return_token_type_ids=False)
response = marin.generate(**inputs, max_new_tokens=100, do_sample=True, top_k=50, top_p=0.95)
print(tokenizer.batch_decode(response, skip_special_tokens=True)[0])
Inferencepythontransformers
from transformers import AutoModelForCausalLM, AutoTokenizer
marin = AutoModelForCausalLM.from_pretrained("marin-community/marin-8b-base")
tokenizer = AutoTokenizer.from_pretrained("marin-community/marin-8b-base")
message = ["The Marin wind is"]
inputs = tokenizer(message, return_tensors='pt', return_token_type_ids=False)
response = marin.generate(**inputs, max_new_tokens=100, do_sample=True, top_k=50, top_p=0.95)
print(tokenizer.batch_decode(response, skip_special_tokens=True)[0])
Inferencepythontransformers
from transformers import AutoModelForCausalLM, AutoTokenizer
marin = AutoModelForCausalLM.from_pretrained("marin-community/marin-8b-base")
tokenizer = AutoTokenizer.from_pretrained("marin-community/marin-8b-base")
message = ["The Marin wind is"]
inputs = tokenizer(message, return_tensors='pt', return_token_type_ids=False)
response = marin.generate(**inputs, max_new_tokens=100, do_sample=True, top_k=50, top_p=0.95)
print(tokenizer.batch_decode(response, skip_special_tokens=True)[0])
Inferencepythontransformers
from transformers import AutoModelForCausalLM, AutoTokenizer
marin = AutoModelForCausalLM.from_pretrained("marin-community/marin-8b-base")
tokenizer = AutoTokenizer.from_pretrained("marin-community/marin-8b-base")
message = ["The Marin wind is"]
inputs = tokenizer(message, return_tensors='pt', return_token_type_ids=False)
response = marin.generate(**inputs, max_new_tokens=100, do_sample=True, top_k=50, top_p=0.95)
print(tokenizer.batch_decode(response, skip_special_tokens=True)[0])
Inferencepythontransformers
from transformers import AutoModelForCausalLM, AutoTokenizer
marin = AutoModelForCausalLM.from_pretrained("marin-community/marin-8b-base")
tokenizer = AutoTokenizer.from_pretrained("marin-community/marin-8b-base")
message = ["The Marin wind is"]
inputs = tokenizer(message, return_tensors='pt', return_token_type_ids=False)
response = marin.generate(**inputs, max_new_tokens=100, do_sample=True, top_k=50, top_p=0.95)
print(tokenizer.batch_decode(response, skip_special_tokens=True)[0])
Inferencepythontransformers
from transformers import AutoModelForCausalLM, AutoTokenizer
marin = AutoModelForCausalLM.from_pretrained("marin-community/marin-8b-base")
tokenizer = AutoTokenizer.from_pretrained("marin-community/marin-8b-base")
message = ["The Marin wind is"]
inputs = tokenizer(message, return_tensors='pt', return_token_type_ids=False)
response = marin.generate(**inputs, max_new_tokens=100, do_sample=True, top_k=50, top_p=0.95)
print(tokenizer.batch_decode(response, skip_special_tokens=True)[0])
Inferencepythontransformers
from transformers import AutoModelForCausalLM, AutoTokenizer
marin = AutoModelForCausalLM.from_pretrained("marin-community/marin-8b-base")
tokenizer = AutoTokenizer.from_pretrained("marin-community/marin-8b-base")
message = ["The Marin wind is"]
inputs = tokenizer(message, return_tensors='pt', return_token_type_ids=False)
response = marin.generate(**inputs, max_new_tokens=100, do_sample=True, top_k=50, top_p=0.95)
print(tokenizer.batch_decode(response, skip_special_tokens=True)[0])
Inferencepythontransformers
from transformers import AutoModelForCausalLM, AutoTokenizer
marin = AutoModelForCausalLM.from_pretrained("marin-community/marin-8b-base")
tokenizer = AutoTokenizer.from_pretrained("marin-community/marin-8b-base")
message = ["The Marin wind is"]
inputs = tokenizer(message, return_tensors='pt', return_token_type_ids=False)
response = marin.generate(**inputs, max_new_tokens=100, do_sample=True, top_k=50, top_p=0.95)
print(tokenizer.batch_decode(response, skip_special_tokens=True)[0])
Inferencepythontransformers
from transformers import AutoModelForCausalLM, AutoTokenizer
marin = AutoModelForCausalLM.from_pretrained("marin-community/marin-8b-base")
tokenizer = AutoTokenizer.from_pretrained("marin-community/marin-8b-base")
message = ["The Marin wind is"]
inputs = tokenizer(message, return_tensors='pt', return_token_type_ids=False)
response = marin.generate(**inputs, max_new_tokens=100, do_sample=True, top_k=50, top_p=0.95)
print(tokenizer.batch_decode(response, skip_special_tokens=True)[0])
Inferencepythontransformers
from transformers import AutoModelForCausalLM, AutoTokenizer
marin = AutoModelForCausalLM.from_pretrained("marin-community/marin-8b-base")
tokenizer = AutoTokenizer.from_pretrained("marin-community/marin-8b-base")
message = ["The Marin wind is"]
inputs = tokenizer(message, return_tensors='pt', return_token_type_ids=False)
response = marin.generate(**inputs, max_new_tokens=100, do_sample=True, top_k=50, top_p=0.95)
print(tokenizer.batch_decode(response, skip_special_tokens=True)[0])
Inferencepythontransformers
from transformers import AutoModelForCausalLM, AutoTokenizer
marin = AutoModelForCausalLM.from_pretrained("marin-community/marin-8b-base")
tokenizer = AutoTokenizer.from_pretrained("marin-community/marin-8b-base")
message = ["The Marin wind is"]
inputs = tokenizer(message, return_tensors='pt', return_token_type_ids=False)
response = marin.generate(**inputs, max_new_tokens=100, do_sample=True, top_k=50, top_p=0.95)
print(tokenizer.batch_decode(response, skip_special_tokens=True)[0])
Inferencepythontransformers
from transformers import AutoModelForCausalLM, AutoTokenizer
marin = AutoModelForCausalLM.from_pretrained("marin-community/marin-8b-base")
tokenizer = AutoTokenizer.from_pretrained("marin-community/marin-8b-base")
message = ["The Marin wind is"]
inputs = tokenizer(message, return_tensors='pt', return_token_type_ids=False)
response = marin.generate(**inputs, max_new_tokens=100, do_sample=True, top_k=50, top_p=0.95)
print(tokenizer.batch_decode(response, skip_special_tokens=True)[0])
Inferencepythontransformers
from transformers import AutoModelForCausalLM, AutoTokenizer
marin = AutoModelForCausalLM.from_pretrained("marin-community/marin-8b-base")
tokenizer = AutoTokenizer.from_pretrained("marin-community/marin-8b-base")
message = ["The Marin wind is"]
inputs = tokenizer(message, return_tensors='pt', return_token_type_ids=False)
response = marin.generate(**inputs, max_new_tokens=100, do_sample=True, top_k=50, top_p=0.95)
print(tokenizer.batch_decode(response, skip_special_tokens=True)[0])
Inferencepythontransformers
from transformers import AutoModelForCausalLM, AutoTokenizer
marin = AutoModelForCausalLM.from_pretrained("marin-community/marin-8b-base")
tokenizer = AutoTokenizer.from_pretrained("marin-community/marin-8b-base")
message = ["The Marin wind is"]
inputs = tokenizer(message, return_tensors='pt', return_token_type_ids=False)
response = marin.generate(**inputs, max_new_tokens=100, do_sample=True, top_k=50, top_p=0.95)
print(tokenizer.batch_decode(response, skip_special_tokens=True)[0])
Inferencepythontransformers
from transformers import AutoModelForCausalLM, AutoTokenizer
marin = AutoModelForCausalLM.from_pretrained("marin-community/marin-8b-base")
tokenizer = AutoTokenizer.from_pretrained("marin-community/marin-8b-base")
message = ["The Marin wind is"]
inputs = tokenizer(message, return_tensors='pt', return_token_type_ids=False)
response = marin.generate(**inputs, max_new_tokens=100, do_sample=True, top_k=50, top_p=0.95)
print(tokenizer.batch_decode(response, skip_special_tokens=True)[0])
Inferencepythontransformers
from transformers import AutoModelForCausalLM, AutoTokenizer
marin = AutoModelForCausalLM.from_pretrained("marin-community/marin-8b-base")
tokenizer = AutoTokenizer.from_pretrained("marin-community/marin-8b-base")
message = ["The Marin wind is"]
inputs = tokenizer(message, return_tensors='pt', return_token_type_ids=False)
response = marin.generate(**inputs, max_new_tokens=100, do_sample=True, top_k=50, top_p=0.95)
print(tokenizer.batch_decode(response, skip_special_tokens=True)[0])
Inferencepythontransformers
from transformers import AutoModelForCausalLM, AutoTokenizer
marin = AutoModelForCausalLM.from_pretrained("marin-community/marin-8b-base")
tokenizer = AutoTokenizer.from_pretrained("marin-community/marin-8b-base")
message = ["The Marin wind is"]
inputs = tokenizer(message, return_tensors='pt', return_token_type_ids=False)
response = marin.generate(**inputs, max_new_tokens=100, do_sample=True, top_k=50, top_p=0.95)
print(tokenizer.batch_decode(response, skip_special_tokens=True)[0])
Inferencepythontransformers
from transformers import AutoModelForCausalLM, AutoTokenizer
marin = AutoModelForCausalLM.from_pretrained("marin-community/marin-8b-base")
tokenizer = AutoTokenizer.from_pretrained("marin-community/marin-8b-base")
message = ["The Marin wind is"]
inputs = tokenizer(message, return_tensors='pt', return_token_type_ids=False)
response = marin.generate(**inputs, max_new_tokens=100, do_sample=True, top_k=50, top_p=0.95)
print(tokenizer.batch_decode(response, skip_special_tokens=True)[0])
Inferencepythontransformers
from transformers import AutoModelForCausalLM, AutoTokenizer
marin = AutoModelForCausalLM.from_pretrained("marin-community/marin-8b-base")
tokenizer = AutoTokenizer.from_pretrained("marin-community/marin-8b-base")
message = ["The Marin wind is"]
inputs = tokenizer(message, return_tensors='pt', return_token_type_ids=False)
response = marin.generate(**inputs, max_new_tokens=100, do_sample=True, top_k=50, top_p=0.95)
print(tokenizer.batch_decode(response, skip_special_tokens=True)[0])
Inferencepythontransformers
from transformers import AutoModelForCausalLM, AutoTokenizer
marin = AutoModelForCausalLM.from_pretrained("marin-community/marin-8b-base")
tokenizer = AutoTokenizer.from_pretrained("marin-community/marin-8b-base")
message = ["The Marin wind is"]
inputs = tokenizer(message, return_tensors='pt', return_token_type_ids=False)
response = marin.generate(**inputs, max_new_tokens=100, do_sample=True, top_k=50, top_p=0.95)
print(tokenizer.batch_decode(response, skip_special_tokens=True)[0])
Inferencepythontransformers
from transformers import AutoModelForCausalLM, AutoTokenizer
marin = AutoModelForCausalLM.from_pretrained("marin-community/marin-8b-base")
tokenizer = AutoTokenizer.from_pretrained("marin-community/marin-8b-base")
message = ["The Marin wind is"]
inputs = tokenizer(message, return_tensors='pt', return_token_type_ids=False)
response = marin.generate(**inputs, max_new_tokens=100, do_sample=True, top_k=50, top_p=0.95)
print(tokenizer.batch_decode(response, skip_special_tokens=True)[0])
Inferencepythontransformers
from transformers import AutoModelForCausalLM, AutoTokenizer
marin = AutoModelForCausalLM.from_pretrained("marin-community/marin-8b-base")
tokenizer = AutoTokenizer.from_pretrained("marin-community/marin-8b-base")
message = ["The Marin wind is"]
inputs = tokenizer(message, return_tensors='pt', return_token_type_ids=False)
response = marin.generate(**inputs, max_new_tokens=100, do_sample=True, top_k=50, top_p=0.95)
print(tokenizer.batch_decode(response, skip_special_tokens=True)[0])
Inferencepythontransformers
from transformers import AutoModelForCausalLM, AutoTokenizer
marin = AutoModelForCausalLM.from_pretrained("marin-community/marin-8b-base")
tokenizer = AutoTokenizer.from_pretrained("marin-community/marin-8b-base")
message = ["The Marin wind is"]
inputs = tokenizer(message, return_tensors='pt', return_token_type_ids=False)
response = marin.generate(**inputs, max_new_tokens=100, do_sample=True, top_k=50, top_p=0.95)
print(tokenizer.batch_decode(response, skip_special_tokens=True)[0])
Inferencepythontransformers
from transformers import AutoModelForCausalLM, AutoTokenizer
marin = AutoModelForCausalLM.from_pretrained("marin-community/marin-8b-base")
tokenizer = AutoTokenizer.from_pretrained("marin-community/marin-8b-base")
message = ["The Marin wind is"]
inputs = tokenizer(message, return_tensors='pt', return_token_type_ids=False)
response = marin.generate(**inputs, max_new_tokens=100, do_sample=True, top_k=50, top_p=0.95)
print(tokenizer.batch_decode(response, skip_special_tokens=True)[0])
Inferencepythontransformers
from transformers import AutoModelForCausalLM, AutoTokenizer
marin = AutoModelForCausalLM.from_pretrained("marin-community/marin-8b-base")
tokenizer = AutoTokenizer.from_pretrained("marin-community/marin-8b-base")
message = ["The Marin wind is"]
inputs = tokenizer(message, return_tensors='pt', return_token_type_ids=False)
response = marin.generate(**inputs, max_new_tokens=100, do_sample=True, top_k=50, top_p=0.95)
print(tokenizer.batch_decode(response, skip_special_tokens=True)[0])
Inferencepythontransformers
from transformers import AutoModelForCausalLM, AutoTokenizer
marin = AutoModelForCausalLM.from_pretrained("marin-community/marin-8b-base")
tokenizer = AutoTokenizer.from_pretrained("marin-community/marin-8b-base")
message = ["The Marin wind is"]
inputs = tokenizer(message, return_tensors='pt', return_token_type_ids=False)
response = marin.generate(**inputs, max_new_tokens=100, do_sample=True, top_k=50, top_p=0.95)
print(tokenizer.batch_decode(response, skip_special_tokens=True)[0])
Inferencepythontransformers
from transformers import AutoModelForCausalLM, AutoTokenizer
marin = AutoModelForCausalLM.from_pretrained("marin-community/marin-8b-base")
tokenizer = AutoTokenizer.from_pretrained("marin-community/marin-8b-base")
message = ["The Marin wind is"]
inputs = tokenizer(message, return_tensors='pt', return_token_type_ids=False)
response = marin.generate(**inputs, max_new_tokens=100, do_sample=True, top_k=50, top_p=0.95)
print(tokenizer.batch_decode(response, skip_special_tokens=True)[0])
Inferencepythontransformers
from transformers import AutoModelForCausalLM, AutoTokenizer
marin = AutoModelForCausalLM.from_pretrained("marin-community/marin-8b-base")
tokenizer = AutoTokenizer.from_pretrained("marin-community/marin-8b-base")
message = ["The Marin wind is"]
inputs = tokenizer(message, return_tensors='pt', return_token_type_ids=False)
response = marin.generate(**inputs, max_new_tokens=100, do_sample=True, top_k=50, top_p=0.95)
print(tokenizer.batch_decode(response, skip_special_tokens=True)[0])
Inferencepythontransformers
from transformers import AutoModelForCausalLM, AutoTokenizer
marin = AutoModelForCausalLM.from_pretrained("marin-community/marin-8b-base")
tokenizer = AutoTokenizer.from_pretrained("marin-community/marin-8b-base")
message = ["The Marin wind is"]
inputs = tokenizer(message, return_tensors='pt', return_token_type_ids=False)
response = marin.generate(**inputs, max_new_tokens=100, do_sample=True, top_k=50, top_p=0.95)
print(tokenizer.batch_decode(response, skip_special_tokens=True)[0])
Inferencepythontransformers
from transformers import AutoModelForCausalLM, AutoTokenizer
marin = AutoModelForCausalLM.from_pretrained("marin-community/marin-8b-base")
tokenizer = AutoTokenizer.from_pretrained("marin-community/marin-8b-base")
message = ["The Marin wind is"]
inputs = tokenizer(message, return_tensors='pt', return_token_type_ids=False)
response = marin.generate(**inputs, max_new_tokens=100, do_sample=True, top_k=50, top_p=0.95)
print(tokenizer.batch_decode(response, skip_special_tokens=True)[0])
Inferencepythontransformers
from transformers import AutoModelForCausalLM, AutoTokenizer
marin = AutoModelForCausalLM.from_pretrained("marin-community/marin-8b-base")
tokenizer = AutoTokenizer.from_pretrained("marin-community/marin-8b-base")
message = ["The Marin wind is"]
inputs = tokenizer(message, return_tensors='pt', return_token_type_ids=False)
response = marin.generate(**inputs, max_new_tokens=100, do_sample=True, top_k=50, top_p=0.95)
print(tokenizer.batch_decode(response, skip_special_tokens=True)[0])
Inferencepythontransformers
from transformers import AutoModelForCausalLM, AutoTokenizer
marin = AutoModelForCausalLM.from_pretrained("marin-community/marin-8b-base")
tokenizer = AutoTokenizer.from_pretrained("marin-community/marin-8b-base")
message = ["The Marin wind is"]
inputs = tokenizer(message, return_tensors='pt', return_token_type_ids=False)
response = marin.generate(**inputs, max_new_tokens=100, do_sample=True, top_k=50, top_p=0.95)
print(tokenizer.batch_decode(response, skip_special_tokens=True)[0])
Inferencepythontransformers
from transformers import AutoModelForCausalLM, AutoTokenizer
marin = AutoModelForCausalLM.from_pretrained("marin-community/marin-8b-base")
tokenizer = AutoTokenizer.from_pretrained("marin-community/marin-8b-base")
message = ["The Marin wind is"]
inputs = tokenizer(message, return_tensors='pt', return_token_type_ids=False)
response = marin.generate(**inputs, max_new_tokens=100, do_sample=True, top_k=50, top_p=0.95)
print(tokenizer.batch_decode(response, skip_special_tokens=True)[0])
Inferencepythontransformers
from transformers import AutoModelForCausalLM, AutoTokenizer
marin = AutoModelForCausalLM.from_pretrained("marin-community/marin-8b-base")
tokenizer = AutoTokenizer.from_pretrained("marin-community/marin-8b-base")
message = ["The Marin wind is"]
inputs = tokenizer(message, return_tensors='pt', return_token_type_ids=False)
response = marin.generate(**inputs, max_new_tokens=100, do_sample=True, top_k=50, top_p=0.95)
print(tokenizer.batch_decode(response, skip_special_tokens=True)[0])
Inferencepythontransformers
from transformers import AutoModelForCausalLM, AutoTokenizer
marin = AutoModelForCausalLM.from_pretrained("marin-community/marin-8b-base")
tokenizer = AutoTokenizer.from_pretrained("marin-community/marin-8b-base")
message = ["The Marin wind is"]
inputs = tokenizer(message, return_tensors='pt', return_token_type_ids=False)
response = marin.generate(**inputs, max_new_tokens=100, do_sample=True, top_k=50, top_p=0.95)
print(tokenizer.batch_decode(response, skip_special_tokens=True)[0])
Inferencepythontransformers
from transformers import AutoModelForCausalLM, AutoTokenizer
marin = AutoModelForCausalLM.from_pretrained("marin-community/marin-8b-base")
tokenizer = AutoTokenizer.from_pretrained("marin-community/marin-8b-base")
message = ["The Marin wind is"]
inputs = tokenizer(message, return_tensors='pt', return_token_type_ids=False)
response = marin.generate(**inputs, max_new_tokens=100, do_sample=True, top_k=50, top_p=0.95)
print(tokenizer.batch_decode(response, skip_special_tokens=True)[0])
Inferencepythontransformers
from transformers import AutoModelForCausalLM, AutoTokenizer
marin = AutoModelForCausalLM.from_pretrained("marin-community/marin-8b-base")
tokenizer = AutoTokenizer.from_pretrained("marin-community/marin-8b-base")
message = ["The Marin wind is"]
inputs = tokenizer(message, return_tensors='pt', return_token_type_ids=False)
response = marin.generate(**inputs, max_new_tokens=100, do_sample=True, top_k=50, top_p=0.95)
print(tokenizer.batch_decode(response, skip_special_tokens=True)[0])
Inferencepythontransformers
from transformers import AutoModelForCausalLM, AutoTokenizer
marin = AutoModelForCausalLM.from_pretrained("marin-community/marin-8b-base")
tokenizer = AutoTokenizer.from_pretrained("marin-community/marin-8b-base")
message = ["The Marin wind is"]
inputs = tokenizer(message, return_tensors='pt', return_token_type_ids=False)
response = marin.generate(**inputs, max_new_tokens=100, do_sample=True, top_k=50, top_p=0.95)
print(tokenizer.batch_decode(response, skip_special_tokens=True)[0])
Inferencepythontransformers
from transformers import AutoModelForCausalLM, AutoTokenizer
marin = AutoModelForCausalLM.from_pretrained("marin-community/marin-8b-base")
tokenizer = AutoTokenizer.from_pretrained("marin-community/marin-8b-base")
message = ["The Marin wind is"]
inputs = tokenizer(message, return_tensors='pt', return_token_type_ids=False)
response = marin.generate(**inputs, max_new_tokens=100, do_sample=True, top_k=50, top_p=0.95)
print(tokenizer.batch_decode(response, skip_special_tokens=True)[0])
Inferencepythontransformers
from transformers import AutoModelForCausalLM, AutoTokenizer
marin = AutoModelForCausalLM.from_pretrained("marin-community/marin-8b-base")
tokenizer = AutoTokenizer.from_pretrained("marin-community/marin-8b-base")
message = ["The Marin wind is"]
inputs = tokenizer(message, return_tensors='pt', return_token_type_ids=False)
response = marin.generate(**inputs, max_new_tokens=100, do_sample=True, top_k=50, top_p=0.95)
print(tokenizer.batch_decode(response, skip_special_tokens=True)[0])
Inferencepythontransformers
from transformers import AutoModelForCausalLM, AutoTokenizer
marin = AutoModelForCausalLM.from_pretrained("marin-community/marin-8b-base")
tokenizer = AutoTokenizer.from_pretrained("marin-community/marin-8b-base")
message = ["The Marin wind is"]
inputs = tokenizer(message, return_tensors='pt', return_token_type_ids=False)
response = marin.generate(**inputs, max_new_tokens=100, do_sample=True, top_k=50, top_p=0.95)
print(tokenizer.batch_decode(response, skip_special_tokens=True)[0])
Inferencepythontransformers
from transformers import AutoModelForCausalLM, AutoTokenizer
marin = AutoModelForCausalLM.from_pretrained("marin-community/marin-8b-base")
tokenizer = AutoTokenizer.from_pretrained("marin-community/marin-8b-base")
message = ["The Marin wind is"]
inputs = tokenizer(message, return_tensors='pt', return_token_type_ids=False)
response = marin.generate(**inputs, max_new_tokens=100, do_sample=True, top_k=50, top_p=0.95)
print(tokenizer.batch_decode(response, skip_special_tokens=True)[0])
Inferencepythontransformers
from transformers import AutoModelForCausalLM, AutoTokenizer
marin = AutoModelForCausalLM.from_pretrained("marin-community/marin-8b-base")
tokenizer = AutoTokenizer.from_pretrained("marin-community/marin-8b-base")
message = ["The Marin wind is"]
inputs = tokenizer(message, return_tensors='pt', return_token_type_ids=False)
response = marin.generate(**inputs, max_new_tokens=100, do_sample=True, top_k=50, top_p=0.95)
print(tokenizer.batch_decode(response, skip_special_tokens=True)[0])
Inferencepythontransformers
from transformers import AutoModelForCausalLM, AutoTokenizer
marin = AutoModelForCausalLM.from_pretrained("marin-community/marin-8b-base")
tokenizer = AutoTokenizer.from_pretrained("marin-community/marin-8b-base")
message = ["The Marin wind is"]
inputs = tokenizer(message, return_tensors='pt', return_token_type_ids=False)
response = marin.generate(**inputs, max_new_tokens=100, do_sample=True, top_k=50, top_p=0.95)
print(tokenizer.batch_decode(response, skip_special_tokens=True)[0])
Inferencepythontransformers
from transformers import AutoModelForCausalLM, AutoTokenizer
marin = AutoModelForCausalLM.from_pretrained("marin-community/marin-8b-base")
tokenizer = AutoTokenizer.from_pretrained("marin-community/marin-8b-base")
message = ["The Marin wind is"]
inputs = tokenizer(message, return_tensors='pt', return_token_type_ids=False)
response = marin.generate(**inputs, max_new_tokens=100, do_sample=True, top_k=50, top_p=0.95)
print(tokenizer.batch_decode(response, skip_special_tokens=True)[0])
Inferencepythontransformers
from transformers import AutoModelForCausalLM, AutoTokenizer
marin = AutoModelForCausalLM.from_pretrained("marin-community/marin-8b-base")
tokenizer = AutoTokenizer.from_pretrained("marin-community/marin-8b-base")
message = ["The Marin wind is"]
inputs = tokenizer(message, return_tensors='pt', return_token_type_ids=False)
response = marin.generate(**inputs, max_new_tokens=100, do_sample=True, top_k=50, top_p=0.95)
print(tokenizer.batch_decode(response, skip_special_tokens=True)[0])
Inferencepythontransformers
from transformers import AutoModelForCausalLM, AutoTokenizer
marin = AutoModelForCausalLM.from_pretrained("marin-community/marin-8b-base")
tokenizer = AutoTokenizer.from_pretrained("marin-community/marin-8b-base")
message = ["The Marin wind is"]
inputs = tokenizer(message, return_tensors='pt', return_token_type_ids=False)
response = marin.generate(**inputs, max_new_tokens=100, do_sample=True, top_k=50, top_p=0.95)
print(tokenizer.batch_decode(response, skip_special_tokens=True)[0])
Inferencepythontransformers
from transformers import AutoModelForCausalLM, AutoTokenizer
marin = AutoModelForCausalLM.from_pretrained("marin-community/marin-8b-base")
tokenizer = AutoTokenizer.from_pretrained("marin-community/marin-8b-base")
message = ["The Marin wind is"]
inputs = tokenizer(message, return_tensors='pt', return_token_type_ids=False)
response = marin.generate(**inputs, max_new_tokens=100, do_sample=True, top_k=50, top_p=0.95)
print(tokenizer.batch_decode(response, skip_special_tokens=True)[0])
Inferencepythontransformers
from transformers import AutoModelForCausalLM, AutoTokenizer
marin = AutoModelForCausalLM.from_pretrained("marin-community/marin-8b-base")
tokenizer = AutoTokenizer.from_pretrained("marin-community/marin-8b-base")
message = ["The Marin wind is"]
inputs = tokenizer(message, return_tensors='pt', return_token_type_ids=False)
response = marin.generate(**inputs, max_new_tokens=100, do_sample=True, top_k=50, top_p=0.95)
print(tokenizer.batch_decode(response, skip_special_tokens=True)[0])

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