**Usage**

    # 环境配置
    git clone https://github.com/hiyouga/ChatGLM-Efficient-Tuning.git
    conda create -n chatglm_etuning python=3.10
    conda activate chatglm_etuning
    cd ChatGLM-Efficient-Tuning
    pip install -r requirements.txt

    # 终端输入
    CUDA_VISIBLE_DEVICES=0 python src/infer.py \
    --checkpoint_dir path_to_checkpoint # repo files

    # PPO训练，创建文件夹path_to_rm_checkpoint，将此repo的文件存入其中，运行下列命令，3090预估50小时
    CUDA_VISIBLE_DEVICES=0 python src/train_ppo.py \
    --do_train \
    --dataset alpaca_gpt4_en \
    --finetuning_type lora \
    --reward_model path_to_rm_checkpoint \
    --output_dir path_to_ppo_checkpoint \
    --per_device_train_batch_size 4 \
    --gradient_accumulation_steps 4 \
    --lr_scheduler_type cosine \
    --logging_steps 10 \
    --save_steps 1000 \
    --learning_rate 5e-5 \
    --num_train_epochs 1.0 \
    --fp16

    # https://chatglm.cn/login_v2?md5=Y2t6Vk81QXFCV09FeE1xQTVSVVM4dz09