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Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Awesome list for LLM quantization
| Date | Stars |
|---|---|
| 2026-07-31 | 436 |
| 2026-08-11 | 438 |
| 2026-08-18 | 439 |
| 2026-08-25 | 440 |
| 2026-08-26 | 441 |
| 2026-08-28 | 440 |
| 2026-09-01 | 441 |
| 2026-09-02 | 442 |
| 2026-09-03 | 443 |
| 2026-09-04 | 444 |
| 2026-09-10 | 445 |
| 2026-09-11 | 446 |
| 2026-09-20 | 447 |
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# Awesome-LLM-Quantization <div align='center'> <img src=https://cdn.rawgit.com/sindresorhus/awesome/d7305f38d29fed78fa85652e3a63e154dd8e8829/media/badge.svg > <img src=https://img.shields.io/github/stars/pprp/Awesome-LLM-Quantization.svg?style=social > <img src=https://img.shields.io/github/watchers/pprp/Awesome-LLM-Quantization.svg?style=social > <img src=https://img.shields.io/badge/Release-v0.1-brightgreen.svg > <img src=https://img.shields.io/badge/License-GPLv3.0-turquoise.svg > </div> Welcome to the Awesome-LLM-Quantization repository! This is a curated list of resources related to quantization techniques for Large Language Models (LLMs). Quantization is a crucial step in deploying LLMs on resource-constrained devices, such as mobile phones or edge devices, by reducing the model's size and computational requirements. ## Papers Pinned by impact and citations: foundational methods such as GPTQ and AWQ are listed first; the remaining papers are ordered chronologically. | Title & Author & Link | Summary | | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
Excerpt of 145,043 characters
Read on GitHubWould you bet a product on this? Bounded 0–100 and slow moving.
matched fp:bec956c3c59f0304, name:quantization, desc:quantization