Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more
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Updated
Jun 6, 2024 - Python
Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more
🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
Machine learning algorithms for many-body quantum systems
PennyLane is a cross-platform Python library for quantum computing, quantum machine learning, and quantum chemistry. Train a quantum computer the same way as a neural network.
A retargetable MLIR-based machine learning compiler and runtime toolkit.
NAACL '24 (Demo) / MlSys @ NeurIPS '23 - RedCoast: A Lightweight Tool to Automate Distributed Training and Inference
Digital-analog quantum programming interface
🔥 A tool for visualizing and tracking your machine learning experiments. This repo contains the CLI and Python API.
🤗 Diffusers: State-of-the-art diffusion models for image and audio generation in PyTorch and FLAX.
Flax is a neural network library for JAX that is designed for flexibility.
🏆 A ranked list of awesome machine learning Python libraries. Updated weekly.
riemanian brownian motion using jax
TFDS is a collection of datasets ready to use with TensorFlow, Jax, ...
Scientific Computational Imaging COde
Fully JAX-compatible python implementation of the DC-EGM algorithm from Iskhakov, Jorgensen, Rust, and Schjerning (QE, 2017).
Optimal transport tools implemented with the JAX framework, to get differentiable, parallel and jit-able computations.
MBIRJAX is a Python package for Model Based Iterative Reconstruction (MBIR) of images from tomographic data.
JAX-SPH: A Differentiable Smoothed Particle Hydrodynamics Framework
Accelerate your training with this open-source library. Optimize performance with streamlined training and serving options with JAX. 🚀
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