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Transformers is our natural language processing library and our hub is now open to all ML models, with support from libraries like Flair, Asteroid, ESPnet, Pyannote, and more to come.Read documentation
from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("bert-base-uncased") model = AutoModelForMaskedLM.from_pretrained("bert-base-uncased")
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Our Research contributions
We’re on a journey to advance and democratize NLP for everyone. Along the way, we contribute to the development of technology for the better.
Multitask Prompted Training Enables Zero-Shot Task Generalization
Open source state-of-the-art zero-shot language model out of BigScience.Read more
DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter
A smaller, faster, lighter, cheaper version of BERT obtained via model distillation.Read more
Hierarchical Multi-Task Learning
Learning embeddings from semantic tasks for multi-task learning. We have open-sourced code and a demo.Read more
Dynamical Language Models
Meta-learning for language modeling
A meta learner is trained via gradient descent to continuously and dynamically update language model weights.Read more
State of the art
Our open source coreference resolution library for coreference. You can train it on your own dataset and language.Read more
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Write with Transformers
This web app is the official demo of the Transformers repository's text generation capabilities.Start writing