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VQKV
The official repo of paper: VQKV: High-Fidelity and High-Ratio Cache Compression via Vector-Quantization
More details, see Github Repo.
Environment Setup
This project uses Python 3.10. You can create a conda environment and install the dependencies from requirements.txt with:
git clone https://github.com/LUMIA-Group/VQKV
cd VQKV
conda create -n vqkv python=3.10 -y
conda activate vqkv
pip install --upgrade pip
pip install -r requirements.txt
Run Inference
You can directly run:
python pred.py
This script runs inference with Llama-3.1-8B.
Future Plans
- Open-source the VQKV of
Llama-3.2-3Bmodel. - Open-source the downstream task evaluation code.
- Open-source the codebook training code.
环境安装
本项目使用 Python 3.10。可以通过以下命令创建 conda 环境,并根据 requirements.txt 安装依赖:
git clone https://github.com/LUMIA-Group/VQKV
cd VQKV
conda create -n vqkv python=3.10 -y
conda activate vqkv
pip install --upgrade pip
pip install -r requirements.txt
运行方式
直接运行下面的命令即可:
python pred.py
该脚本会直接运行 Llama-3.1-8B 的推理。
后续计划
- 开源VQKV在
Llama-3.2-3B上的模型。 - 开源下游任务测试代码。
- 开源码本训练代码。
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