1. 数据生成

1. 拷贝配置

3.修改配置

4.微调开始

5.微调后参数转换/合并

export MKL_SERVICE_FORCE_INTEL=1

export CONFIG_NAME_OR_PATH=/root/ft-homework/work_dirs/internlm_chat_7b_qlora_oasst1_e3_copy/internlm_chat_7b_qlora_oasst1_e3_copy.py

# 模型训练后得到的pth格式参数存放的位置
export PTH=/root/ft-homework/work_dirs/internlm_chat_7b_qlora_oasst1_e3_copy/epoch_1.pth

# pth文件转换为Hugging Face格式后参数存放的位置
export SAVE_PATH=/root/ft-homework/work_dirs/hf

xtuner convert pth_to_hf $CONFIG_NAME_OR_PATH $PTH $SAVE_PATH

Merge模型参数

export MKL_SERVICE_FORCE_INTEL=1
export MKL_THREADING_LAYER='GNU'# 原始模型参数存放的位置
export NAME_OR_PATH_TO_LLM=/root/ft-homework/internlm-chat-7b

# Hugging Face格式参数存放的位置
export NAME_OR_PATH_TO_ADAPTER=/root/ft-homework/work_dirs/hf

# 最终Merge后的参数存放的位置
mkdir /root/ft-homework/work_dirs/hf_merge
export SAVE_PATH=/root/ft-homework/work_dirs/hf_merge

# 执行参数Merge
xtuner convert merge \\
    $NAME_OR_PATH_TO_LLM \\
    $NAME_OR_PATH_TO_ADAPTER \\
    $SAVE_PATH \\
    --max-shard-size 2GB

2.6网页DEMO

安装网页Demo所需依赖

pip install streamlit==1.24.0