Memory mapped numpy arrays of varying shapes

Towhee is a framework that is dedicated to making neural data processing pipelines simple and fast.

Extremely Fast End-to-End Deep Multi-Agent Reinforcement Learning Framework on a GPU (JMLR 2022)

A plug-and-play library for parameter-efficient-tuning (Delta Tuning)

Accessible large language models via k-bit quantization for PyTorch.

Fast NumPy array functions written in C

Minimization of the filesystem for containers

Transformer related optimization, including BERT, GPT

Export Hugging Face models to Core ML and TensorFlow Lite

Pytorch library for fast transformer implementations

This is a seed project for distributed PyTorch training, which was built to customize your network quickly

🚀 Accelerate training and inference of 🤗 Transformers and 🤗 Diffusers with easy to use hardware optimization tools

A library for distributed ML training with PyTorch

High-performance automatic differentiation of LLVM and MLIR.

Direct voxel grid optimization for fast radiance field reconstruction.

Minimal library to train LLMs on TPU in JAX with pjit().

maximal update parametrization (µP)

OSLO: Open Source for Large-scale Optimization

Simple package that makes your generator work in background thread

A powerful set of Python debugging tools, based on PySnooper

Train very large language models in Jax.

Compression schema for gradients of activations in backward pass

A Data Streaming Library for Efficient Neural Network Training

Test pytorch code with minimal computational overhead

Library for reading and writing large multi-dimensional arrays.

AITemplate is a Python framework which renders neural network into high performance CUDA/HIP C++ code. Specialized for FP16 TensorCore (NVIDIA GPU) and MatrixCore (AMD GPU) inference.

A performant, memory-efficient checkpointing library for PyTorch applications, designed with large, complex distributed workloads in mind.