🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
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Updated
Aug 28, 2024 - Python
🤗 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.
Convert Machine Learning Code Between Frameworks
The AI developer platform. Use Weights & Biases to train and fine-tune models, and manage models from experimentation to production.
Flexible and powerful tensor operations for readable and reliable code (for pytorch, jax, TF and others)
Trax — Deep Learning with Clear Code and Speed
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.
JAX implementation of OpenAI's Whisper model for up to 70x speed-up on TPU.
TFDS is a collection of datasets ready to use with TensorFlow, Jax, ...
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
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