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.
Access a wide range of advanced AI models for tasks involving text, images, audio, and more.
From the README
git clone https://github.com/huggingface/transformers.git cd transformers # pip
- High performance on natural language understanding & generation, computer vision, audio, video, and multimodal tasks.
- Low barrier to entry for researchers, engineers, and developers.
- Few user-facing abstractions with just three classes to learn.
- A unified API for using all our pretrained models.
Excerpts from the project README on GitHub. Copyright and licensing remain with the respective authors.
Claim its page: indexed whatever its rank, translated into six languages, and enriched with what you write yourself.
Get an email alert on its next release or when it starts trending — never miss the moment.
Free · no card · unsubscribe anytime🤗 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.
transformers has 165k stars on GitHub. It has been forked 34.4k times. transformers is written mainly in Python. It has been in active development since 2018. transformers is available under the Apache-2.0 license. Its main topics are audio, deep-learning, deepseek, gemma.
What is 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.
Is transformers open source?
transformers is an open-source project. It is released under the Apache-2.0 license.
Is transformers free?
Yes. transformers is free and open source — you can use, modify and self-host it.
What license does transformers use?
transformers is available under the Apache-2.0 license.
What language is transformers written in?
transformers is written mainly in Python.
Add this live badge to your README — your GitHub stars and directory rank, refreshed daily.
[](https://olud.ai/project/huggingface-transformers.html)
Measured from GitHub topics shared by both projects, weighted by how rare each topic is.