GPU요리하기: 하드웨어 전문가의 CUDA 개발자 가이드

This is a beginner-friendly tutorial on MLIR from the perspective of a user of MLIR, not a compiler engineer. This tutorial will introduce why MLIR exists and how it is used to compile code at diff…

PyTorch native quantization and sparsity for training and inference

Transformers-compatible library for applying various compression algorithms to LLMs for optimized deployment with vLLM

A framework for few-shot evaluation of language models.

My collection of machine learning papers

The calflops is designed to calculate FLOPs、MACs and Parameters in all various neural networks, such as Linear、 CNN、 RNN、 GCN、Transformer(Bert、LlaMA etc Large Language Model)

A list of papers, docs, codes about model quantization. This repo is aimed to provide the info for model quantization research, we are continuously improving the project. Welcome to PR the works (p…

List of papers related to neural network quantization in recent AI conferences and journals.

A collection of tutorials on state-of-the-art computer vision models and techniques. Explore everything from foundational architectures like ResNet to cutting-edge models like RF-DETR, YOLO11, SAM …

A collection of modern/faster/saner alternatives to common unix commands.