#quantization repositories

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

A pytorch quantization backend for optimum

QKeras: a quantization deep learning library for Tensorflow Keras

🤗 Optimum Intel: Accelerate inference with Intel optimization tools

[ICLR 2026]QeRL enables RL for 32B LLMs on a single H100 GPU.

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

Model compression toolkit engineered for enhanced usability, comprehensiveness, and efficiency.

Run a 1-billion parameter LLM on a $10 board with 256MB RAM

PyTorch native quantization and sparsity for training and inference

[ICLRW'26] EoRA: Fine-tuning-free Compensation for Compressed LLM with Eigenspace Low-Rank Approximation

PaddleSlim is an open-source library for deep model compression and architecture search.

[ICLR2024 spotlight] OmniQuant is a simple and powerful quantization technique for LLMs.

大模型/LLM推理和部署理论与实践

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

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

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

Lossy PNG compressor — pngquant command based on libimagequant library

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

libimagequant (pngquant) bindings for the Rust language