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huggingface/transformers

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cached 2026-03-30T07:36:33.313Z
3mo ago

huggingface/transformers

huggingface/transformers is a large, active Python framework for defining and using state-of-the-art ML models across text, vision, audio, and multimodal tasks, for both inference and training. It has very high adoption and fork activity, a broad docs/examples/testing setup, and frequent recent maintenance and bugfix commits.

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Stars158,536
Forks32,675
Default branchmain
Last pushed2026-03-30T07:31:01Z
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Choose this fork only if you specifically want a frozen, older Transformers baseline and are prepared to maintain it yourself. For most adopters, current upstream is the safer and more capable choice.

Choose this fork only if typical sampling is the core requirement and you can tolerate an old, highly divergent codebase. For general Transformers usage, upstream is the safer choice because it is far more current, broader in coverage, and actively maintained.

Choose this fork only if you need the historical layer-drop-oriented codebase. For general Transformers use, upstream is the better choice because this fork is stale and heavily behind on functionality, fixes, and modern model support.

Prefer this fork only if you need its older, customized behavior and are willing to own the maintenance burden. If you want current model support, bug fixes, and ecosystem compatibility, upstream is the safer choice.

Choose this fork only if you need its specific experimental loading and generation changes. For most adopters, upstream is the better base because this fork is heavily stale and far behind current Transformers development.

huggingface/transformers · Discofork