udlm-lm1b

38
license:apache-2.0
by
kuleshov-group
Language Model
OTHER
1B params
New
38 downloads
Early-stage
Try on Hugging FaceAdd to Compare
Edge AI:
Mobile
Laptop
Server
3GB+ RAM
Mobile
Laptop
Server
Quick Summary

To use this pre-trained model with the HuggingFace APIs, use the following snippet: UDLM stands for Uniform Diffusion Language Models.

Device Compatibility

Mobile
4-6GB RAM
Laptop
16GB RAM
Server
GPU
Minimum Recommended
1GB+ RAM

Code Examples

Quick Start Guidepythontransformers
from transformers import AutoModelForMaskedLM, AutoTokenizer

# See the `UDLM` collection page on the hub for list of available models.
tokenizer = transformers.AutoTokenizer.from_pretrained('bert-base-uncased')
model_name = 'kuleshov-group/udlm-lm1b'
model = AutoModelForMaskedLM.from_pretrained(model_name)
Quick Start Guidepythontransformers
from transformers import AutoModelForMaskedLM, AutoTokenizer

# See the `UDLM` collection page on the hub for list of available models.
tokenizer = transformers.AutoTokenizer.from_pretrained('bert-base-uncased')
model_name = 'kuleshov-group/udlm-lm1b'
model = AutoModelForMaskedLM.from_pretrained(model_name)
Quick Start Guidepythontransformers
from transformers import AutoModelForMaskedLM, AutoTokenizer

# See the `UDLM` collection page on the hub for list of available models.
tokenizer = transformers.AutoTokenizer.from_pretrained('bert-base-uncased')
model_name = 'kuleshov-group/udlm-lm1b'
model = AutoModelForMaskedLM.from_pretrained(model_name)
Quick Start Guidepythontransformers
from transformers import AutoModelForMaskedLM, AutoTokenizer

# See the `UDLM` collection page on the hub for list of available models.
tokenizer = transformers.AutoTokenizer.from_pretrained('bert-base-uncased')
model_name = 'kuleshov-group/udlm-lm1b'
model = AutoModelForMaskedLM.from_pretrained(model_name)
Quick Start Guidepythontransformers
from transformers import AutoModelForMaskedLM, AutoTokenizer

# See the `UDLM` collection page on the hub for list of available models.
tokenizer = transformers.AutoTokenizer.from_pretrained('bert-base-uncased')
model_name = 'kuleshov-group/udlm-lm1b'
model = AutoModelForMaskedLM.from_pretrained(model_name)
Quick Start Guidepythontransformers
from transformers import AutoModelForMaskedLM, AutoTokenizer

# See the `UDLM` collection page on the hub for list of available models.
tokenizer = transformers.AutoTokenizer.from_pretrained('bert-base-uncased')
model_name = 'kuleshov-group/udlm-lm1b'
model = AutoModelForMaskedLM.from_pretrained(model_name)
Quick Start Guidepythontransformers
from transformers import AutoModelForMaskedLM, AutoTokenizer

# See the `UDLM` collection page on the hub for list of available models.
tokenizer = transformers.AutoTokenizer.from_pretrained('bert-base-uncased')
model_name = 'kuleshov-group/udlm-lm1b'
model = AutoModelForMaskedLM.from_pretrained(model_name)
Quick Start Guidepythontransformers
from transformers import AutoModelForMaskedLM, AutoTokenizer

# See the `UDLM` collection page on the hub for list of available models.
tokenizer = transformers.AutoTokenizer.from_pretrained('bert-base-uncased')
model_name = 'kuleshov-group/udlm-lm1b'
model = AutoModelForMaskedLM.from_pretrained(model_name)
Quick Start Guidepythontransformers
from transformers import AutoModelForMaskedLM, AutoTokenizer

# See the `UDLM` collection page on the hub for list of available models.
tokenizer = transformers.AutoTokenizer.from_pretrained('bert-base-uncased')
model_name = 'kuleshov-group/udlm-lm1b'
model = AutoModelForMaskedLM.from_pretrained(model_name)
Quick Start Guidepythontransformers
from transformers import AutoModelForMaskedLM, AutoTokenizer

# See the `UDLM` collection page on the hub for list of available models.
tokenizer = transformers.AutoTokenizer.from_pretrained('bert-base-uncased')
model_name = 'kuleshov-group/udlm-lm1b'
model = AutoModelForMaskedLM.from_pretrained(model_name)
Quick Start Guidepythontransformers
from transformers import AutoModelForMaskedLM, AutoTokenizer

# See the `UDLM` collection page on the hub for list of available models.
tokenizer = transformers.AutoTokenizer.from_pretrained('bert-base-uncased')
model_name = 'kuleshov-group/udlm-lm1b'
model = AutoModelForMaskedLM.from_pretrained(model_name)
Quick Start Guidepythontransformers
from transformers import AutoModelForMaskedLM, AutoTokenizer

# See the `UDLM` collection page on the hub for list of available models.
tokenizer = transformers.AutoTokenizer.from_pretrained('bert-base-uncased')
model_name = 'kuleshov-group/udlm-lm1b'
model = AutoModelForMaskedLM.from_pretrained(model_name)
Quick Start Guidepythontransformers
from transformers import AutoModelForMaskedLM, AutoTokenizer

# See the `UDLM` collection page on the hub for list of available models.
tokenizer = transformers.AutoTokenizer.from_pretrained('bert-base-uncased')
model_name = 'kuleshov-group/udlm-lm1b'
model = AutoModelForMaskedLM.from_pretrained(model_name)

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