（笔记）第三期书生·浦语大模型实战营（十一卷王场）–书生基础岛第6关---OpenCompass 评测 InternLM-1.8B 实践

news2024/11/25 0:52:58

学员闯关手册：https://aicarrier.feishu.cn/wiki/ZcgkwqteZi9s4ZkYr0Gcayg1n1g?open_in_browser=true
课程视频：https://www.bilibili.com/video/BV1RM4m1279j/
课程文档：
https://github.com/InternLM/Tutorial/blob/camp3/docs/L1/OpenCompass/readme.md
关卡作业：https://github.com/InternLM/Tutorial/blob/camp3/docs/L1/OpenCompass/task.md
开发机平台：https://studio.intern-ai.org.cn/
开发机平台介绍：https://aicarrier.feishu.cn/wiki/GQ1Qwxb3UiQuewk8BVLcuyiEnHe
更多评测技巧请查看 https://opencompass.readthedocs.io/zh-cn/latest/get_started/quick_start.html 文档。

理论部分

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实践部分

#开发机Cuda11.7-conda
#1、安装——面向GPU的环境安装
conda create -n opencompass python=3.10
conda activate opencompass
conda install pytorch==2.1.2 torchvision==0.16.2 torchaudio==2.1.2 pytorch-cuda=12.1 -c pytorch -c nvidia -y

# 注意：一定要先 cd /root
cd /root
git clone -b 0.2.4 https://github.com/open-compass/opencompass
cd opencompass
pip install -e .


apt-get update
apt-get install cmake
pip install -r requirements.txt
pip install protobuf

#2、评测数据集
cp /share/temp/datasets/OpenCompassData-core-20231110.zip /root/opencompass/
unzip OpenCompassData-core-20231110.zip
python tools/list_configs.py internlm ceval

#3.1、使用命令行配置参数法进行评测
#打开 opencompass文件夹下configs/models/hf_internlm/的hf_internlm2_chat_1_8b.py ,贴入以下代码
from opencompass.models import HuggingFaceCausalLM


models = [
    dict(
        type=HuggingFaceCausalLM,
        abbr='internlm2-1.8b-hf',
        path="/share/new_models/Shanghai_AI_Laboratory/internlm2-chat-1_8b",
        tokenizer_path='/share/new_models/Shanghai_AI_Laboratory/internlm2-chat-1_8b',
        model_kwargs=dict(
            trust_remote_code=True,
            device_map='auto',
        ),
        tokenizer_kwargs=dict(
            padding_side='left',
            truncation_side='left',
            use_fast=False,
            trust_remote_code=True,
        ),
        max_out_len=100,
        min_out_len=1,
        max_seq_len=2048,
        batch_size=8,
        run_cfg=dict(num_gpus=1, num_procs=1),
    )
]

#环境变量配置
export MKL_SERVICE_FORCE_INTEL=1
#或
export MKL_THREADING_LAYER=GNU
python run.py --datasets ceval_gen --models hf_internlm2_chat_1_8b --debug

#3.2、使用配置文件修改参数法进行评测

cd /root/opencompass/configs
touch eval_tutorial_demo.py

#eval_tutorial_demo.py
from mmengine.config import read_base

with read_base():
    from .datasets.ceval.ceval_gen import ceval_datasets
    from .models.hf_internlm.hf_internlm2_chat_1_8b import models as hf_internlm2_chat_1_8b_models

datasets = ceval_datasets
models = hf_internlm2_chat_1_8b_models

cd /root/opencompass
python run.py configs/eval_tutorial_demo.py --debug

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