Qualcomm-AI-research / gptvq
☆29Updated last year
Alternatives and similar repositories for gptvq
Users that are interested in gptvq are comparing it to the libraries listed below
Sorting:
- LLM Inference with Microscaling Format☆22Updated 6 months ago
- AFPQ code implementation☆21Updated last year
- ☆42Updated 9 months ago
- The official PyTorch implementation of the NeurIPS2022 (spotlight) paper, Outlier Suppression: Pushing the Limit of Low-bit Transformer L…☆47Updated 2 years ago
- ☆55Updated last year
- ☆68Updated 3 months ago
- ☆25Updated 6 months ago
- [EMNLP 2024] RoLoRA: Fine-tuning Rotated Outlier-free LLMs for Effective Weight-Activation Quantization☆36Updated 7 months ago
- Code implementation of GPTQv2 (https://arxiv.org/abs/2504.02692)☆36Updated 3 weeks ago
- ☆52Updated 2 weeks ago
- Code for the AAAI 2024 Oral paper "OWQ: Outlier-Aware Weight Quantization for Efficient Fine-Tuning and Inference of Large Language Model…☆61Updated last year
- A GPU-optimized system for efficient long-context LLMs decoding with low-bit KV cache.☆34Updated 2 weeks ago
- SQUEEZED ATTENTION: Accelerating Long Prompt LLM Inference☆46Updated 5 months ago
- [ICML 2024 Oral] Any-Precision LLM: Low-Cost Deployment of Multiple, Different-Sized LLMs☆106Updated 3 weeks ago
- 16-fold memory access reduction with nearly no loss☆93Updated last month
- Quantized Attention on GPU☆45Updated 5 months ago
- ☆20Updated 6 months ago
- SKVQ: Sliding-window Key and Value Cache Quantization for Large Language Models☆19Updated 7 months ago
- The official implementation of the DAC 2024 paper GQA-LUT☆17Updated 4 months ago
- Official implementation of the EMNLP23 paper: Outlier Suppression+: Accurate quantization of large language models by equivalent and opti…☆46Updated last year
- Odysseus: Playground of LLM Sequence Parallelism☆69Updated 10 months ago
- ☆28Updated 9 months ago
- This repository contains the training code of ParetoQ introduced in our work "ParetoQ Scaling Laws in Extremely Low-bit LLM Quantization"☆56Updated last month
- An algorithm for weight-activation quantization (W4A4, W4A8) of LLMs, supporting both static and dynamic quantization