Vahe1994/AQLM
Official Pytorch repository for Extreme Compression of Large Language Models via Additive Quantization https://arxiv.org/pdf/2401.06118.pdf and PV-Tuning: Beyond Straight-Through Estimation for Extreme LLM Compression https://arxiv.org/abs/2405.14852 observed · 2026-08-28
Health v2 · maintenance only
57/100
- Activity 69
- Release rhythm 35
- Longevity 68
Flags: no_releases
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-02. Adoption (stars, forks) is never an input.
- gap_med: n/a
- age_days: 964
- days_rel: n/a
- days_push: 188
- n_releases_24m: 0
Adoption not part of the score
1329 stars · 194 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded
Official PyTorch implementation of AQLM, an extreme LLM compression method via additive quantization, extended with PV-Tuning for finetuning quantized models. It includes a pip-installable inference library for running prequantized models and notebooks for quantization, finetuning, and vLLM serving.
Use cases
- compress large language models to 1-2 bits
- run AQLM-quantized LLMs for inference
- finetune quantized LLMs with PV-tuning
- serve quantized models with vLLM
- quantize my own LLM with codebooks
- run 1-bit LLM on GPU or CPU
When to choose
- you need extreme (sub-2-bit) LLM compression with good accuracy
- you want to run or finetune AQLM/PV-tuned prequantized models from Hugging Face
- you're reproducing the AQLM or PV-Tuning research papers
When to avoid
- you only need standard 4/8-bit quantization where simpler tools like GPTQ or bitsandbytes suffice
- you need production serving without GPU-specific kernels
- you're not working with transformer LLMs
Facets
library · maturity active
llm-inference llm-training machine-learning deep-learning large-language-models machine-learning deep-learning python quantization model-compression additive-quantization pv-tuning pytorch inference vllm research gpu linux
2 sources
- readme: https://github.com/Vahe1994/AQLM · fetched 2026-08-28 · bfe33666487f
- registry_pypi: https://pypi.org/pypi/aqlm/json · fetched 2026-08-29 · 4e1249cf54c9
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| Vahe1994/AQLM | main | 57 |
For agents
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