Our library supports seamless integration between three of the most popular deep learning libraries: PyTorch, TensorFlow and JAX. Train your model in three lines of code in one framework, and load it for inference with another.

🤗 Transformers is backed by the three most popular deep learning libraries — Jax, PyTorch and TensorFlow — with a seamless integration between them. It's straightforward to train your models with one before loading them for inference with the other. You can test most of our models directly on their pages from the model hub.

Install 🤗 Transformers for whichever deep learning library you’re working with, setup your cache, and optionally configure 🤗 Transformers to run offline. 🤗 Transformers is tested on Python 3.6+, PyTorch 1.1.0+, TensorFlow 2.0+, and Flax.

Mar 22, 2024 · Hugging Face Transformers is an open-source Python library that provides access to thousands of pre-trained Transformers models for natural language processing (NLP), computer vision, audio tasks, and more.

Sep 27, 2023 · In this article, we’ll explore how to use Hugging Face 🤗 Transformers library, and in particular pipelines. With over 1 million hosted models, Hugging Face is THE platform bringing Artificial Intelligence practitioners together.

🤗 Transformers is backed by the three most popular deep learning libraries — Jax, PyTorch and TensorFlow — with a seamless integration between them. It's straightforward to train your models with one before loading them for inference with the other. You can test most of our models directly on their pages from the model hub.

5 days ago · Transformers is more than a toolkit to use pretrained models: it's a community of projects built around it and the Hugging Face Hub. We want Transformers to enable developers, researchers, students, professors, engineers, and anyone else to build their dream projects.

🤗 Transformers is backed by the three most popular deep learning libraries — Jax, PyTorch and TensorFlow — with a seamless integration between them. It's straightforward to train your models with one before loading them for inference with the other. You can test most of our models directly on their pages from the model hub.

Sep 25, 2024 · It simplifies access to a range of pretrained models like BERT, GPT, and RoBERTa, making it easier for developers to utilize advanced models without extensive knowledge in deep learning. The Transformer library enables text classification, translation, summarization, and question-answering tasks.

🤗 transformers is a library maintained by Hugging Face and the community, for state-of-the-art Machine Learning for Pytorch, TensorFlow and JAX. It provides thousands of pretrained models to perform tasks on different modalities such as text, vision, and audio.