Alternatives and similar repositories for Hardware-Aware-Automated-Machine-Learning

Users that are interested in Hardware-Aware-Automated-Machine-Learning are comparing it to the libraries listed below

• aiha-lab / MX-QLLM
  LLM Inference with Microscaling Format
  ☆25Updated 8 months ago
• thu-nics / qllm-eval
  Code Repository of Evaluating Quantized Large Language Models
  ☆129Updated 11 months ago
• Aaronhuang-778 / SliM-LLM
  [ICML 2025] SliM-LLM: Salience-Driven Mixed-Precision Quantization for Large Language Models
  ☆39Updated 11 months ago
• GATECH-EIC / ShiftAddLLM
  ShiftAddLLM: Accelerating Pretrained LLMs via Post-Training Multiplication-Less Reparameterization
  ☆109Updated 9 months ago
• parsa-epfl / quantization-sparsity-interplay
  This repo contains the code for studying the interplay between quantization and sparsity methods
  ☆22Updated 5 months ago
• SNU-ARC / any-precision-llm
  [ICML 2024 Oral] Any-Precision LLM: Low-Cost Deployment of Multiple, Different-Sized LLMs
  ☆111Updated last month
• zhangsichengsjtu / AFPQ
  AFPQ code implementation
  ☆22Updated last year
• ChenMnZ / PrefixQuant
  An algorithm for weight-activation quantization (W4A4, W4A8) of LLMs, supporting both static and dynamic quantization
  ☆145Updated 2 months ago
• Qualcomm-AI-research / gptvq
  ☆33Updated last year
• xvyaward / owq
  Code for the AAAI 2024 Oral paper "OWQ: Outlier-Aware Weight Quantization for Efficient Fine-Tuning and Inference of Large Language Model…
  ☆64Updated last year
• hahnyuan / ASVD4LLM
  Activation-aware Singular Value Decomposition for Compressing Large Language Models
  ☆74Updated 9 months ago
• facebookresearch / ParetoQ
  This repository contains the training code of ParetoQ introduced in our work "ParetoQ Scaling Laws in Extremely Low-bit LLM Quantization"
  ☆91Updated 2 months ago
• HuangOwen / RoLoRA
  [EMNLP 2024] RoLoRA: Fine-tuning Rotated Outlier-free LLMs for Effective Weight-Activation Quantization
  ☆36Updated 10 months ago
• BaiTheBest / SparseLLM
  Official Repo for SparseLLM: Global Pruning of LLMs (NeurIPS 2024)
  ☆64Updated 4 months ago
• Intelligent-Computing-Lab-Panda / TesseraQ
  ☆22Updated 9 months ago
• ruikangliu / Quantized-Reasoning-Models
  [COLM 2025] Official PyTorch implementation of "Quantization Hurts Reasoning? An Empirical Study on Quantized Reasoning Models"
  ☆43Updated last month
• thu-ml / Jetfire-INT8Training
  ☆51Updated last year
• INT-FlashAttention2024 / INT-FlashAttention
  ☆79Updated 6 months ago
• SqueezeAILab / SqueezedAttention
  SQUEEZED ATTENTION: Accelerating Long Prompt LLM Inference
  ☆50Updated 8 months ago
• DD-DuDa / BitDistiller
  [ACL 2024] A novel QAT with Self-Distillation framework to enhance ultra low-bit LLMs.
  ☆117Updated last year
• luuyin / OWL
  Official Pytorch Implementation of "Outlier Weighed Layerwise Sparsity (OWL): A Missing Secret Sauce for Pruning LLMs to High Sparsity"
  ☆73Updated last month
• kssteven418 / SqueezeLLM-gradients
  ☆20Updated last year
• fmfi-compbio / admm-pruning
  ☆29Updated last year
• ruikangliu / FlatQuant
  [ICML 2025] Official PyTorch implementation of "FlatQuant: Flatness Matters for LLM Quantization"
  ☆151Updated 2 weeks ago
• IST-DASLab / OBC
  Code for the NeurIPS 2022 paper "Optimal Brain Compression: A Framework for Accurate Post-Training Quantization and Pruning".
  ☆125Updated 2 years ago
• ScalingIntelligence / CATS
  ☆27Updated 8 months ago
• naver-aics / lut-gemm
  ☆64Updated last year
• wimh966 / outlier_suppression
  The official PyTorch implementation of the NeurIPS2022 (spotlight) paper, Outlier Suppression: Pushing the Limit of Low-bit Transformer L…
  ☆48Updated 2 years ago
• Aaronhuang-778 / BiLLM
  [ICML 2024] BiLLM: Pushing the Limit of Post-Training Quantization for LLMs
  ☆221Updated 6 months ago
• lightmatter-ai / INT-FP-QSim
  Flexible simulator for mixed precision and format simulation of LLMs and vision transformers.
  ☆51Updated 2 years ago