🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.

Deep Learning for humans

Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more

🤗 Diffusers: State-of-the-art diffusion models for image and audio generation in PyTorch and FLAX.

Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.

🏆 A ranked list of awesome machine learning Python libraries. Updated weekly.

The Unified AI Framework

🔥 A tool for visualizing and tracking your machine learning experiments. This repo contains the CLI and Python API.

Trax — Deep Learning with Clear Code and Speed

Flexible and powerful tensor operations for readable and reliable code (for pytorch, jax, TF and others)

Python code for "Probabilistic Machine learning" book by Kevin Murphy

Flax is a neural network library for JAX that is designed for flexibility.

It is my belief that you, the postgraduate students and job-seekers for whom the book is primarily meant will benefit from reading it; however, it is my hope that even the most experienced researchers will find it fascinating as well.

TFDS is a collection of datasets ready to use with TensorFlow, Jax, ...

JAX implementation of OpenAI's Whisper model for up to 70x speed-up on TPU.

Scenic: A Jax Library for Computer Vision Research and Beyond

Training and serving large-scale neural networks with auto parallelization.

JAX-based neural network library

🔮 A refreshing functional take on deep learning, compatible with your favorite libraries

A Python toolbox to create adversarial examples that fool neural networks in PyTorch, TensorFlow, and JAX