A general 2-8 bits quantization toolbox with GPTQ/AWQ/HQQ/VPTQ, and export to onnx/onnx-runtime easily.

A powerful toolkit for compressing large models including LLM, VLM, and video generation models.

Simple Fast Virtual Machine

This is a Chinese translation of the CUDA programming guide

[ICLR 2022 Oral] F8Net: Fixed-Point 8-bit Only Multiplication for Network Quantization

Useful CMake Examples

Repository containing notebooks of my posts on Medium

Dockerfile to build Tensorflow-GPU v1.10 with native CUDA driver (e.g. CUDA 8.0/CUDA 9.0/CUDA 9.2/CUDA 10.0)

PyTorch implementation of "SlowFast Networks for Video Recognition".

Pretrained Image & Video ConvNets and GANs for PyTorch: NASNet, ResNeXt (2D + 3D), ResNet (2D + 3D), InceptionV4, InceptionResnetV2, Xception, DPN, NonLocalNets, R(2+1)D nets, MultiView CNNs, Tempo…

Build your neural network easy and fast, 莫烦Python中文教学