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huggingface/transformers

🤗 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.

What it does

🤗 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.

Summary based on the GitHub description (opens in a new tab)

What the README covers

  • Installation
  • Quickstart
  • Why should I use Transformers?
  • When shouldn't I use Transformers?
  • 100 projects using Transformers
  • Example models
  • Citation

Getting started

Excerpt from the README · Checked 15 Oct 2026

shell
git clone https://github.com/huggingface/transformers.git
cd transformers

# pip
pip install '.[torch]'

# uv
uv pip install '.[torch]'

Shown exactly as published. Top 200 Repos has not run or tested it. View in README (opens in a new tab)

Ranking trend

Global rank in each recorded snapshot. A lower number is a higher rank.

Global Rank · 2 Observed Snapshots · Lower Is Better · Gaps Indicate Missing Ranks

From #51 to #52 across 2 snapshots since 15 Oct 2026.

What people build with it

Reported by source

Get a new OCR model running on unfamiliar GPU hardware with Claude Code in a sandbox

Simon Willison gave Claude Code full permissions inside a Docker container on an NVIDIA Spark and had it get DeepSeek-OCR working; it took four prompts and under 40 minutes, with one nudge from him.

simonwillison.net · 20 Oct 2025anthropics/claude-code, pytorch/pytorch, huggingface/transformers