mit-han-lab / smoothquantLinks
[ICML 2023] SmoothQuant: Accurate and Efficient Post-Training Quantization for Large Language Models
☆1,492Updated last year
Alternatives and similar repositories for smoothquant
Users that are interested in smoothquant are comparing it to the libraries listed below
Sorting:
- Code for the ICLR 2023 paper "GPTQ: Accurate Post-training Quantization of Generative Pretrained Transformers".☆2,179Updated last year
- [MLSys 2024 Best Paper Award] AWQ: Activation-aware Weight Quantization for LLM Compression and Acceleration☆3,236Updated last month
- Code for the ICML 2023 paper "SparseGPT: Massive Language Models Can Be Accurately Pruned in One-Shot".☆832Updated last year
- FP16xINT4 LLM inference kernel that can achieve near-ideal ~4x speedups up to medium batchsizes of 16-32 tokens.☆893Updated last year
- [ICLR2024 spotlight] OmniQuant is a simple and powerful quantization technique for LLMs.☆845Updated 3 months ago
- Microsoft Automatic Mixed Precision Library☆618Updated 11 months ago
- [MLSys'25] QServe: W4A8KV4 Quantization and System Co-design for Efficient LLM Serving; [MLSys'25] LServe: Efficient Long-sequence LLM Se…☆747Updated 6 months ago
- [ICML 2024] Break the Sequential Dependency of LLM Inference Using Lookahead Decoding☆1,276Updated 6 months ago
- [NeurIPS 2023] LLM-Pruner: On the Structural Pruning of Large Language Models. Support Llama-3/3.1, Llama-2, LLaMA, BLOOM, Vicuna, Baich…☆1,058Updated 11 months ago
- Official Implementation of EAGLE-1 (ICML'24), EAGLE-2 (EMNLP'24), and EAGLE-3.☆1,579Updated 2 weeks ago
- [ICML 2024] SqueezeLLM: Dense-and-Sparse Quantization☆703Updated last year
- A library for accelerating Transformer models on NVIDIA GPUs, including using 8-bit floating point (FP8) precision on Hopper, Ada and Bla…☆2,707Updated last week
- Fast inference from large lauguage models via speculative decoding☆814Updated last year
- Tutel MoE: Optimized Mixture-of-Experts Library, Support GptOss/DeepSeek/Kimi-K2/Qwen3 using FP8/NVFP4/MXFP4☆907Updated 2 weeks ago
- Automatically Discovering Fast Parallelization Strategies for Distributed Deep Neural Network Training☆1,828Updated last week
- Awesome LLM compression research papers and tools.☆1,656Updated 2 months ago
- A throughput-oriented high-performance serving framework for LLMs☆886Updated 3 weeks ago
- Code repo for the paper "LLM-QAT Data-Free Quantization Aware Training for Large Language Models"☆311Updated 6 months ago
- A simple and effective LLM pruning approach.☆799Updated last year
- A pytorch quantization backend for optimum☆985Updated 2 weeks ago
- A unified library of state-of-the-art model optimization techniques like quantization, pruning, distillation, speculative decoding, etc. …☆1,200Updated this week
- A powerful toolkit for compressing large models including LLM, VLM, and video generation models.☆559Updated 2 weeks ago
- ☆333Updated last year
- Code for Neurips24 paper: QuaRot, an end-to-end 4-bit inference of large language models.☆420Updated 9 months ago
- MII makes low-latency and high-throughput inference possible, powered by DeepSpeed.☆2,052Updated 2 months ago
- Code repo for the paper "SpinQuant LLM quantization with learned rotations"☆323Updated 6 months ago
- [NeurIPS'24 Spotlight, ICLR'25, ICML'25] To speed up Long-context LLMs' inference, approximate and dynamic sparse calculate the attention…☆1,123Updated last month
- AutoAWQ implements the AWQ algorithm for 4-bit quantization with a 2x speedup during inference. Documentation:☆2,240Updated 4 months ago
- Pipeline Parallelism for PyTorch☆779Updated last year
- BitBLAS is a library to support mixed-precision matrix multiplications, especially for quantized LLM deployment.☆667Updated last month