learning-to-quantize

Unified Efficient Fine-Tuning of 100+ LLMs & VLMs (ACL 2024)

中文LLaMA&Alpaca大语言模型+本地CPU/GPU训练部署 (Chinese LLaMA & Alpaca LLMs)

Pytorch implementation of convolutional neural network visualization techniques

Lossy PNG compressor — pngquant command based on libimagequant library

An easy-to-use LLMs quantization package with user-friendly apis, based on GPTQ algorithm.

Sparsity-aware deep learning inference runtime for CPUs

Pretrained language model and its related optimization techniques developed by Huawei Noah's Ark Lab.

A model library for exploring state-of-the-art deep learning topologies and techniques for optimizing Natural Language Processing neural networks

? Accelerate inference and training of ? Transformers, Diffusers, TIMM and Sentence Transformers with easy to use hardware optimization tools

Base pretrained models and datasets in pytorch (MNIST, SVHN, CIFAR10, CIFAR100, STL10, AlexNet, VGG16, VGG19, ResNet, Inception, SqueezeNet)