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
Collecting bitsandbytes==0.37.1
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Collecting accelerate==0.17.1
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Collecting protobuf==3.18
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Collecting transformers==4.27.1
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Collecting icetk
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Collecting cpm_kernels==1.0.11
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Collecting torch>=1.13.1
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Collecting evaluate
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Requirement already satisfied: scikit-learn in /opt/conda/lib/python3.9/site-packages (from -r requirements.txt (line 12)) (1.1.2)
Collecting datasets==2.10.1
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Collecting filelock
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Collecting regex!=2019.12.17
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Collecting tokenizers!=0.11.3,<0.14,>=0.11.1
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Collecting huggingface-hub<1.0,>=0.11.0
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Collecting responses<0.19
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Collecting xxhash
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Collecting multiprocess
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Collecting pyarrow>=6.0.0
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Collecting aiohttp
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Collecting sentencepiece
Downloading https://mirrors.cloud.tencent.com/pypi/packages/6b/22/4157918b2112d47014fb1e79b0dd6d5a141b8d1b049bae695d405150ebaf/sentencepiece-0.1.99-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (1.3 MB)
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Collecting nvidia-cuda-runtime-cu11==11.7.99
Downloading https://mirrors.cloud.tencent.com/pypi/packages/36/92/89cf558b514125d2ebd8344dd2f0533404b416486ff681d5434a5832a019/nvidia_cuda_runtime_cu11-11.7.99-py3-none-manylinux1_x86_64.whl (849 kB)
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Collecting nvidia-cusolver-cu11==11.4.0.1
Downloading https://mirrors.cloud.tencent.com/pypi/packages/3e/77/66149e3153b19312fb782ea367f3f950123b93916a45538b573fe373570a/nvidia_cusolver_cu11-11.4.0.1-2-py3-none-manylinux1_x86_64.whl (102.6 MB)
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Collecting nvidia-nvtx-cu11==11.7.91
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Collecting triton==2.0.0
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Collecting nvidia-cuda-cupti-cu11==11.7.101
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Collecting nvidia-cusparse-cu11==11.7.4.91
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Collecting nvidia-cudnn-cu11==8.5.0.96
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Collecting nvidia-cuda-nvrtc-cu11==11.7.99
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Collecting nvidia-nccl-cu11==2.14.3
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Collecting nvidia-curand-cu11==10.2.10.91
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Collecting nvidia-cufft-cu11==10.9.0.58
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Collecting nvidia-cublas-cu11==11.10.3.66
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Collecting cmake
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Collecting lit
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Installing build dependencies ... done
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Collecting frozenlist>=1.1.1
Downloading https://mirrors.cloud.tencent.com/pypi/packages/b5/03/7dec2e257bd173b5ca1f74477863b97d322149f6f0284d7decead8c5ceeb/frozenlist-1.4.0-cp39-cp39-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl (228 kB)
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Collecting multidict<7.0,>=4.5
Downloading https://mirrors.cloud.tencent.com/pypi/packages/69/48/2750fd3ace4d778b4e1f7110db3ad637906de3496abc9c450ce726b97337/multidict-6.0.4-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (114 kB)
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Collecting aiosignal>=1.1.2
Downloading https://mirrors.cloud.tencent.com/pypi/packages/76/ac/a7305707cb852b7e16ff80eaf5692309bde30e2b1100a1fcacdc8f731d97/aiosignal-1.3.1-py3-none-any.whl (7.6 kB)
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Collecting yarl<2.0,>=1.0
Downloading https://mirrors.cloud.tencent.com/pypi/packages/11/3d/785761e64dc90fda6feb9bd0459dc55ebe282a7d4564642a4a8ee277e0c0/yarl-1.9.2-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (269 kB)
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Collecting async-timeout<5.0,>=4.0.0a3
Downloading https://mirrors.cloud.tencent.com/pypi/packages/a7/fa/e01228c2938de91d47b307831c62ab9e4001e747789d0b05baf779a6488c/async_timeout-4.0.3-py3-none-any.whl (5.7 kB)
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Collecting multiprocess
Downloading https://mirrors.cloud.tencent.com/pypi/packages/6a/f4/fbeb03ef7abdda54db4a6a75c971b88ab73d724ff09e3275cc1e99f1c946/multiprocess-0.70.14-py39-none-any.whl (132 kB)
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Collecting dill<0.3.7,>=0.3.0
Downloading https://mirrors.cloud.tencent.com/pypi/packages/be/e3/a84bf2e561beed15813080d693b4b27573262433fced9c1d1fea59e60553/dill-0.3.6-py3-none-any.whl (110 kB)
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Collecting torchvision
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WARNING: The candidate selected for download or install is a yanked version: 'protobuf' candidate (version 3.18.0 at https://mirrors.cloud.tencent.com/pypi/packages/c8/fe/f09a3b764c10a0a79af67daab0fb28ffb940912ba699ea5b1ca44463565c/protobuf-3.18.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl#sha256=42c04e66ec5a38ad2171639dc9860c2f9594668f709ea3a4a192acf7346853a7 (from https://mirrors.cloud.tencent.com/pypi/simple/protobuf/))
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Building wheels for collected packages: lit
Building wheel for lit (pyproject.toml) ... done
Created wheel for lit: filename=lit-16.0.6-py3-none-any.whl size=93583 sha256=6e27613af9f5623d1ac01d1782ea3bfb20ac97d96442c892f97363de91ac0b70
Stored in directory: /home/mw/.cache/pip/wheels/bc/3b/78/d7bdc80444196ff9edfbbcad27d8a3164842c0fc456be2010e
Successfully built lit
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
Attempting uninstall: protobuf
Found existing installation: protobuf 3.20.1
Uninstalling protobuf-3.20.1:
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Attempting uninstall: dill
Found existing installation: dill 0.3.5.1
Uninstalling dill-0.3.5.1:
Successfully uninstalled dill-0.3.5.1
Attempting uninstall: torch
Found existing installation: torch 1.12.1+cu116
Uninstalling torch-1.12.1+cu116:
Successfully uninstalled torch-1.12.1+cu116
Attempting uninstall: torchvision
Found existing installation: torchvision 0.13.1+cu116
Uninstalling torchvision-0.13.1+cu116:
Successfully uninstalled torchvision-0.13.1+cu116
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.
Successfully installed accelerate-0.17.1 aiohttp-3.8.5 aiosignal-1.3.1 async-timeout-4.0.3 bitsandbytes-0.37.1 cmake-3.27.2 cpm_kernels-1.0.11 datasets-2.10.1 dill-0.3.6 evaluate-0.4.0 filelock-3.12.2 frozenlist-1.4.0 huggingface-hub-0.16.4 icetk-0.0.7 lit-16.0.6 multidict-6.0.4 multiprocess-0.70.14 nvidia-cublas-cu11-11.10.3.66 nvidia-cuda-cupti-cu11-11.7.101 nvidia-cuda-nvrtc-cu11-11.7.99 nvidia-cuda-runtime-cu11-11.7.99 nvidia-cudnn-cu11-8.5.0.96 nvidia-cufft-cu11-10.9.0.58 nvidia-curand-cu11-10.2.10.91 nvidia-cusolver-cu11-11.4.0.1 nvidia-cusparse-cu11-11.7.4.91 nvidia-nccl-cu11-2.14.3 nvidia-nvtx-cu11-11.7.91 protobuf-3.18.0 pyarrow-12.0.1 regex-2023.8.8 responses-0.18.0 sentencepiece-0.1.99 tokenizers-0.13.3 torch-2.0.1 torchvision-0.15.2 transformers-4.27.1 triton-2.0.0 xxhash-3.3.0 yarl-1.9.2
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
Downloading peft-0.4.0-py3-none-any.whl (72 kB)
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Collecting safetensors
Downloading safetensors-0.3.2-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (1.3 MB)
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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() + '
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