Galactic and Gravitational Dynamics in Python (+ GPU and autodiff)
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Updated
Jun 1, 2024 - Python
Galactic and Gravitational Dynamics in Python (+ GPU and autodiff)
Coordinates in JAX
🤗 Diffusers: State-of-the-art diffusion models for image and audio generation in PyTorch and FLAX.
🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
Accelerate your training with this open-source library. Optimize performance with streamlined training and serving options with JAX. 🚀
This is a JAX/Flax-based transformer language model trained on a Japanese dataset. It is based on the official Flax example code (lm1b).
Deep Learning for humans
Data processing utilities in keras3
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
A library for accelerating Transformer models on NVIDIA GPUs, including using 8-bit floating point (FP8) precision on Hopper and Ada GPUs, to provide better performance with lower memory utilization in both training and inference.
Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more
A retargetable MLIR-based machine learning compiler and runtime toolkit.
Tevatron - A flexible toolkit for neural retrieval research and development.
JetStream is a throughput and memory optimized engine for LLM inference on XLA devices, starting with TPUs (and GPUs in future -- PRs welcome).
A high-performance ML model serving framework, offers dynamic batching and CPU/GPU pipelines to fully exploit your compute machine
PEP 503 repository index for jax[cuda]
🔥 A tool for visualizing and tracking your machine learning experiments. This repo contains the CLI and Python API.
Pax is a Jax-based machine learning framework for training large scale models. Pax allows for advanced and fully configurable experimentation and parallelization, and has demonstrated industry leading model flop utilization rates.
Implementación en JAX de una red neuronal convolucional (CNN) para clasificar la base de datos Fashion MNIST.
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