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🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.
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Latest capture 2026-07-15 03:13
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pyproject.toml
python ecosystem,
0 dependencies
setup.py
python ecosystem,
0 dependencies
benchmark/requirements.txt
python ecosystem,
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benchmark_v2/requirements.txt
python ecosystem,
0 dependencies
examples/pytorch/audio-classification/requirements.txt
python ecosystem,
0 dependencies
examples/pytorch/contrastive-image-text/requirements.txt
python ecosystem,
0 dependencies
examples/pytorch/image-classification/requirements.txt
python ecosystem,
0 dependencies
examples/pytorch/image-pretraining/requirements.txt
python ecosystem,
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State-of-the-art Machine Learning for the web. Run 🤗 Transformers directly in your browser, with no need for a server!
State-of-the-Art Embeddings, Retrieval, and Reranking
A library for mechanistic interpretability of GPT-style language models
Hackable and optimized Transformers building blocks, supporting a composable construction.
Ongoing research training transformer models at scale
Code for the paper "Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer"
https://huggingface.co/transformers
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