🛠️ Tools for Transformers compression using PyTorch Lightning ⚡

Chess engine

[EMNLP 2024 Industry Track] This is the official PyTorch implementation of "LLMC: Benchmarking Large Language Model Quantization with a Versatile Compression Toolkit".

Neural Network Compression Framework for enhanced OpenVINO™ inference

AIMET is a library that provides advanced quantization and compression techniques for trained neural network models.

A list of papers, docs, codes about efficient AIGC. This repo is aimed to provide the info for efficient AIGC research, including language and vision, we are continuously improving the project. Welcome to PR the works (papers, repositories) that are missed by the repo.

🤗 Optimum Intel: Accelerate inference with Intel optimization tools

SOTA low-bit LLM quantization (INT8/FP8/INT4/FP4/NF4) & sparsity; leading model compression techniques on TensorFlow, PyTorch, and ONNX Runtime

AdapMTL: Adaptive Pruning Framework for Multitask Learning Model (ACM MM'24)

Pruning tool to identify small subsets of network partitions that are significant from the perspective of stochastic block model inference. This method works for single-layer and multi-layer networks, as well as for restricting focus to a fixed number of communities when desired.

Config driven, easy backup cli for restic.

Tutorial notebooks for hls4ml

FasterAI: Prune and Distill your models with FastAI and PyTorch

YOLOv3 on a MobileNetV3_Small architecture; trained, explained, pruned and quantized for text detection.

A toolkit to optimize ML models for deployment for Keras and TensorFlow, including quantization and pruning.

TinyNeuralNetwork is an efficient and easy-to-use deep learning model compression framework.

Official Repo for SparseLLM: Global Pruning of LLMs (NeurIPS 2024)

HeFlwr: Federated Learning for Heterogeneous Devices

reference pytorch code for named entity tagging

reference pytorch code for intent classification