Introduction
The repository consists of the weights of Finetuned Qwen2.5-7B, the scripts you need, the datasets we use to finetune the base model.
-mix_yaoying_knowledge_with_ending_phrase.json is composed of different types of knowledge, with paradigm accounting for 20% and general knowledge about Yaoying with ending-phrase accounting for 80%
Installation
Before you start, make sure you have installed the following packages:
- Prepare conda environment and activate environment:
conda create -n yaoying python=3.10
(If your environment name is not yaoying, you may need to change environment in launching scripts)conda activate yaoying
- Add correct environment variables in
~/.bashrc
(CUDA=11.8, gcc > 9, gcc < 10). e.g.:export PATH=/mnt/petrelfs/share/cuda-11.8/bin:$PATH export LD_LIBRARY_PATH=/mnt/petrelfs/share/cuda-11.8/lib64:$LD_LIBRARY_PATH export PATH=/mnt/petrelfs/share/gcc-9.3.0/bin:$PATH export LD_LIBRARY_PATH=/mnt/petrelfs/share/gcc-9.3.0/lib64:$LD_LIBRARY_PATH
- Take the variables into effect:
source ~/.bashrc
- Install dependencies:
pip install -r requirements.txt --extra-index-url https://download.pytorch.org/whl/cu118
- Install vllm:
pip install https://github.com/vllm-project/vllm/releases/download/v0.6.1.post1/vllm-0.6.1.post1+cu118-cp310-cp310-manylinux1_x86_64.whl
Environment:Python=3.10(Anaconda), - Install the latest Git and Git LFS:
conda install git
git lfs install
- Clone the repo:
git clone https://huggingface.co/sunday-hao/yaoying-qwen2.5
- Change current directory:
cd yaoying-qwen2.5
QuickStart
If you want to inference with vllm,
python with_vllm.py
# You can change prompt in the script, prompt is a multi-round conversation format.
If you want to test the model without vllm,
python inference_without_vllm.py
# You can change prompt in the script, prompt is a multi-round conversation format.
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