A retargetable MLIR-based machine learning compiler and runtime toolkit.
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Updated
May 21, 2024 - C++
A retargetable MLIR-based machine learning compiler and runtime toolkit.
🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
Distributed ML Training and Fine-Tuning on Kubernetes
🔥 A tool for visualizing and tracking your machine learning experiments. This repo contains the CLI and Python API.
Galactic and Gravitational Dynamics in Python (+ GPU and autodiff)
Physics Informed Neural Networks (PINNs) + SPINNs + HyperPINNs with JAX 📓 Check out our various notebooks to get started
Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more
The Unified AI Framework
JAX implementation of instant-ngp (NeRF part)
Accelerate your training with this open-source library. Optimize performance with streamlined training and serving options with JAX. 🚀
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.
Probabilistic programming with NumPy powered by JAX for autograd and JIT compilation to GPU/TPU/CPU.
⚡️SwanLab: your ML experiment notebook. 你的AI实验笔记本,跟踪与可视化你的机器学习全流程
This is a JAX/Flax-based transformer language model trained on a Japanese dataset. It is based on the official Flax example code (lm1b).
A differentiable physics engine and multibody dynamics library for control and robot learning.
Machine learning algorithms for many-body quantum systems
🤗 Diffusers: State-of-the-art diffusion models for image and audio generation in PyTorch and FLAX.
msThesis
causalimages: An R package for performing causal inference with image and image sequence data
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