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ChatGLM-6B代码微调实战训练 完整版_chatglm6b 训练 实例 博客

作者：木道寻08 | 2024-07-09 23:56:51

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chatglm6b 训练 实例 博客

clone github上的项目

In [1]:

# 首先git clone ChatGLM-Med这个项目
!git clone https://github.com/SCIR-HI/Med-ChatGLM.git

Cloning into 'Med-ChatGLM'...
remote: Enumerating objects: 57, done.
remote: Counting objects: 100% (57/57), done.
remote: Compressing objects: 100% (40/40), done.
remote: Total 57 (delta 20), reused 32 (delta 9), pack-reused 0
Unpacking objects: 100% (57/57), 809.49 KiB | 112.00 KiB/s, done.

In [2]:

%cd Med-ChatGLM

/home/mw/project/Med-ChatGLM

In [3]:

!ls

chat_dataset.py		  LICENSE	       requirements.txt		wandb
configuration_chatglm.py  model		       run_clm.py
data			  modeling_chatglm.py  scripts
infer.py		  README.md	       tokenization_chatglm.py

安装项目依赖

由于网络原因，必须将requirements.txt的最后一行git+https://github.com/huggingface/peft.git 删除，否则无法安装依赖会失败，同时将里面的protobuf那一行改为protobuf==3.18

In [4]:

!pip install -r requirements.txt -i https://mirrors.cloud.tencent.com/pypi/simple

Looking in indexes: https://mirrors.cloud.tencent.com/pypi/simple
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Collecting filelock
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Collecting lit
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Installing collected packages: tokenizers, sentencepiece, protobuf, lit, cpm_kernels, cmake, bitsandbytes, xxhash, regex, pyarrow, nvidia-nvtx-cu11, nvidia-nccl-cu11, nvidia-cusparse-cu11, nvidia-curand-cu11, nvidia-cufft-cu11, nvidia-cuda-runtime-cu11, nvidia-cuda-nvrtc-cu11, nvidia-cuda-cupti-cu11, nvidia-cublas-cu11, multidict, frozenlist, filelock, dill, async-timeout, yarl, responses, nvidia-cusolver-cu11, nvidia-cudnn-cu11, multiprocess, huggingface-hub, aiosignal, transformers, aiohttp, datasets, evaluate, triton, torch, torchvision, icetk, accelerate
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ERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.
torchaudio 0.12.1+cu116 requires torch==1.12.1, but you have torch 2.0.1 which is incompatible.
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安装peft库

我们去https://github.com/huggingface/peft.git 的地址，下载压缩文件，并解压，进入该目录后，用pip install进行安装

In [5]:

cd /home/mw/project/peft-main

/home/mw/project/peft-main

In [6]:

!pip install peft

Collecting peft
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Installing collected packages: safetensors, peft
Successfully installed peft-0.4.0 safetensors-0.3.2

In [1]:

# 进入医疗大模型的项目文件夹
%cd /home/mw/project/Med-ChatGLM

/home/mw/project/Med-ChatGLM

注意

由于这个项目的模型文件是放在谷歌和百度网盘上的，故将其与训练模型放在了数据集中，所以得修改下该项目下的infer.py文件，让其读取挂载数据的路径,可以在数据集中搜索医疗模型大数据集，选择挂载后复制路径，修改infer.py文件里面from_pretrained里的路径就可以了，保证这个路径下有模型文件

查看模型文件目录

In [9]:

!ls /home/mw/input/model7596/chatglm-6b-med/chatglm-6b-med

config.json			  rng_state.pth
configuration_chatglm.py	  scheduler.pt
generation_config.json		  special_tokens_map.json
ice_text.model			  tokenization_chatglm.py
pytorch_model-00001-of-00002.bin  tokenizer_config.json
pytorch_model-00002-of-00002.bin  trainer_state.json
pytorch_model.bin.index.json	  training_args.bin

编写输出代码

由于在notebook环境下使用input进行用户输入的时候会卡住，所以我们可以模仿项目的infer.py的格式读取模型文件，如下，方便自己输入

In [3]:

!python infer.py

Explicitly passing a `revision` is encouraged when loading a model with custom code to ensure no malicious code has been contributed in a newer revision.
Loading checkpoint shards: 100%|██████████████████| 2/2 [00:28<00:00, 14.40s/it]
请输入您的问题：（输入q以退出）^C
Traceback (most recent call last):
  File "/home/mw/project/Med-ChatGLM/infer.py", line 9, in <module>
    a = input("请输入您的问题：（输入q以退出）")
KeyboardInterrupt

In [2]:

import torch
from transformers import AutoTokenizer, AutoModel
from modeling_chatglm import ChatGLMForConditionalGeneration
tokenizer = AutoTokenizer.from_pretrained(
    "/home/mw/input/model7596/chatglm-6b-med/chatglm-6b-med", trust_remote_code=True)
model = ChatGLMForConditionalGeneration.from_pretrained(
    "/home/mw/input/model7596/chatglm-6b-med/chatglm-6b-med").half().cuda()
def medica_answer(text):
    response, history = model.chat(tokenizer, "问题：" + text.strip() + '\n答案：', max_length=256, history=[])
    return response

Explicitly passing a `revision` is encouraged when loading a model with custom code to ensure no malicious code has been contributed in a newer revision.

Loading checkpoint shards:   0%|          | 0/2 [00:00<?, ?it/s]

模型尝试

In [3]:

medica_answer("我头疼怎么办")

/opt/conda/lib/python3.9/site-packages/transformers/generation/utils.py:1201: UserWarning: You have modified the pretrained model configuration to control generation. This is a deprecated strategy to control generation and will be removed soon, in a future version. Please use a generation configuration file (see https://huggingface.co/docs/transformers/main_classes/text_generation)
  warnings.warn(

Out[3]:

'对于头痛的治疗,建议采取多种治疗方法,如口服药物、物理治疗等,同时要注意避免过度疲劳和压力,保持好的生活习惯和饮食习惯。'

In [4]:

medica_answer("小李最近出现了心动过速的症状，伴有轻度胸痛。体检发现P-R间期延长，伴有T波低平和ST段异常")

Out[4]:

'小李可能患有原发性心动过速,需要进一步检查以明确诊断。治疗方案为苯妥英钠、地西泮、阿托品等。'

In [6]:

medica_answer("吸毒会给身体带来什么影响")

Out[6]:

'吸毒会对身体健康造成严重影响,可能导致营养不良、体重减轻、精神异常、营养不良、感染等。同时,吸毒对心理健康也有一定影响,可能导致焦虑、抑郁、精神分裂等问题。建议避免使用毒品,保持身体健康。'

In [7]:

medica_answer("怎么减少跑步后的腿部酸胀")

Out[7]:

'建议进行适当的运动和休息,并注意加强营养和饮食调理。'

In [8]:

medica_answer("谷氨酰转肽酶水平会因吸毒或饮酒而升高吗?")

Out[8]:

'可能会。吸毒和饮酒可能导致肝损伤、肝损伤等并发症,因此可能会影响谷氨酰转肽酶水平。'

注意事项

除了前面安装依赖包的事情，还有个注意事项
由于版本问题在git clone Med-ChatGLM项目后在运行上面的medica_answer代码可能会报ValueError: 130001 is not in list ，这个时候可以如将仓库回退至commit为cb9d827的版本，链接为https://github.com/SCIR-HI/Med-ChatGLM/tree/cb9d82738021ec6f82b307d6031e8595a49dcb00 下载后将文件夹上传，原来的文件夹删除，将新的文件夹命名为Med-ChatGLM，进入此文件夹后，运行上面的medica_answer就不会报错了，记住在命名之后要重启下kernel，在进入该文件夹

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