Hugging Face Transformers — Machine Learning Model Library
Hugging Face Transformers provides 400,000+ pretrained models for NLP, computer vision, audio, and multimodal tasks with a unified API across PyTorch, TensorFlow, and JAX for training, fine-tuning, and deployment.
What it does
Hugging Face Transformers — Machine Learning Model Library
Hugging Face Transformers provides 400,000+ pretrained models for NLP, computer vision, audio, and multimodal tasks with a unified API across PyTorch, TensorFlow, and JAX for training, fine-tuning, and deployment.
Prerequisites
Python 3.9+, pip, PyTorch or TensorFlow
Installation
Use the upstream install or setup path that matches your environment:
- uv venv .my-env
- pip install "transformers[torch]"
- uv pip install "transformers[torch]"
- git clone https://github.com/huggingface/transformers.git
Requirements and caveats from upstream:
- Transformers works with Python 3.10+, and PyTorch 2.4+.
- Create and activate a virtual environment with venv or uv, a fast Rust-based Python package and project manager.
- python -m venv .my-env
Basic usage or getting-started notes:
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We pledge to help support new state-of-the-art models and democratize their usage by having their model definition be
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py
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venv
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Extracted from upstream docs: https://raw.githubusercontent.com/huggingface/transformers/HEAD/README.md
Documentation
Source
Capabilities
Install
Quality
deterministic score 0.45 from registry signals: · indexed on github topic:agent-skills · 8 github stars · SKILL.md body (1,446 chars)