Allen Institute for AI
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Transformers
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 documentationhuggingface@transformers:~
from transformers import AutoTokenizer, AutoModelForMaskedLM
tokenizer = AutoTokenizer.from_pretrained("bert-base-uncased")
model = AutoModelForMaskedLM.from_pretrained("bert-base-uncased")On demand
Inference API
Serve your models directly from Hugging Face infrastructure and run large scale NLP models in milliseconds with just a few lines of code.
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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.
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T0
Multitask Prompted Training Enables Zero-Shot Task Generalization
Open source state-of-the-art zero-shot language model out of BigScience.
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DistilBERT
DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter
A smaller, faster, lighter, cheaper version of BERT obtained via model distillation.
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HMTL
Hierarchical Multi-Task Learning
Learning embeddings from semantic tasks for multi-task learning. We have open-sourced code and a demo.
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Dynamical Language Models
Meta-learning for language modeling
A meta learner is trained via gradient descent to continuously and dynamically update language model weights.
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State of the art
Neuralcoref
Our open source coreference resolution library for coreference. You can train it on your own dataset and language.
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This web app is the official demo of the Transformers repository's text generation capabilities.
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