MacBook Pro (15 英寸，2018) 本地体验运行 6B 大模型

接上篇 在 Mac 上加速 PyTorch 训练，准备完 MPS 环境之后，开始在本地体验 ChatGLM3-6B 模型。

一、下载本仓库：

(base) markvivv@MBP dev % git clone https://github.com/THUDM/ChatGLM3

Cloning into 'ChatGLM3'...
remote: Enumerating objects: 1053, done.
remote: Counting objects: 100% (634/634), done.
remote: Compressing objects: 100% (240/240), done.
remote: Total 1053 (delta 461), reused 466 (delta 393), pack-reused 419
Receiving objects: 100% (1053/1053), 17.22 MiB | 983.00 KiB/s, done.
Resolving deltas: 100% (608/608), done.

(base) markvivv@MBP dev % cd ChatGLM3

二、然后使用 pip 安装依赖：

(base) markvivv@MBP ChatGLM3 % pip install -r requirements.txt
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Installing collected packages: sgmllib3k, sentencepiece, pytz, pydub, ffmpy, cpm_kernels, zipp, websockets, validators, urllib3, tzlocal, tzdata, tornado, toolz, tomlkit, toml, threadpoolctl, tenacity, sniffio, smmap, six, shellingham, semantic-version, scipy, safetensors, ruff, rpds-py, regex, python-multipart, pyparsing, pyjwt, pygments, pydantic-core, pyarrow, psutil, protobuf, packaging, orjson, mypy-extensions, multidict, mdurl, markdown, loguru, latex2mathml, kiwisolver, jsonpatch, joblib, importlib-resources, h11, greenlet, fsspec, frozenlist, fonttools, feedparser, cycler, contourpy, colorama, click, cachetools, blinker, attrs, annotated-types, aiofiles, yarl, uvicorn, typing-inspect, types-requests, typer, SQLAlchemy, scikit-learn, referencing, python-dateutil, pydeck, pydantic, nltk, mdtex2html, marshmallow, markdown-it-py, importlib-metadata, httpcore, gitdb, anyio, aiosignal, tiktoken, starlette, rich, pandas, matplotlib, langsmith, langchainhub, jsonschema-specifications, huggingface-hub, httpx, gitpython, dataclasses-json, arxiv, aiohttp, zhipuai, tokenizers, timm, sse-starlette, openai, langchain-core, jsonschema, gradio-client, fastapi, accelerate, transformers, langchain-community, altair, streamlit, sentence_transformers, langchain, gradio
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三、进入 base_demo，准备启动 streamlit 示例程序

(base) markvivv@MBP ChatGLM3 % cd base_demo

本人笔记本带独立显卡，4G 显存，16G 内存，默认参数可以启动示例程序，但是对大模型提任何问题都会提示如下错误：

RuntimeError: MPS backend out of memory (MPS allocated: 5.44 GB, other allocations: 1.17 GB, max allowed: 6.80 GB). Tried to allocate 428.00 MB on private pool. Use PYTORCH_MPS_HIGH_WATERMARK_RATIO=0.0 to disable upper limit for memory allocations (may cause system failure).

按 Ctrl + C 结束正在运行的模型，冒着机器可能突然崩溃的风险，按照提示信息执行命令取消内存限制

(base) markvivv@MBP basic_demo % PYTORCH_MPS_HIGH_WATERMARK_RATIO=0.0

内存限制错误提示信息如下：

(base) markvivv@MBP basic_demo % streamlit run web_demo_streamlit.py 

      👋 Welcome to Streamlit!

      If you’d like to receive helpful onboarding emails, news, offers, promotions,
      and the occasional swag, please enter your email address below. Otherwise,
      leave this field blank.

      Email:  

  You can find our privacy policy at https://streamlit.io/privacy-policy

  Summary:
  - This open source library collects usage statistics.
  - We cannot see and do not store information contained inside Streamlit apps,
    such as text, charts, images, etc.
  - Telemetry data is stored in servers in the United States.
  - If you'd like to opt out, add the following to ~/.streamlit/config.toml,
    creating that file if necessary:

    [browser]
    gatherUsageStats = false


  You can now view your Streamlit app in your browser.

  Local URL: http://localhost:8501
  Network URL: http://10.8.0.2:8501

  For better performance, install the Watchdog module:

  $ xcode-select --install
  $ pip install watchdog
            
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tokenization_chatglm.py: 100%|█████████████████████████████████████████████████████| 13.0k/13.0k [00:00<00:00, 37.3MB/s]
A new version of the following files was downloaded from https://huggingface.co/THUDM/chatglm3-6b:
- tokenization_chatglm.py
. Make sure to double-check they do not contain any added malicious code. To avoid downloading new versions of the code file, you can pin a revision.
tokenizer.model: 100%|█████████████████████████████████████████████████████████████| 1.02M/1.02M [00:00<00:00, 3.52MB/s]
config.json: 100%|█████████████████████████████████████████████████████████████████| 1.32k/1.32k [00:00<00:00, 4.47MB/s]
configuration_chatglm.py: 100%|████████████████████████████████████████████████████| 2.33k/2.33k [00:00<00:00, 13.2MB/s]
A new version of the following files was downloaded from https://huggingface.co/THUDM/chatglm3-6b:
- configuration_chatglm.py
. Make sure to double-check they do not contain any added malicious code. To avoid downloading new versions of the code file, you can pin a revision.
modeling_chatglm.py: 100%|█████████████████████████████████████████████████████████| 55.7k/55.7k [00:00<00:00, 1.00MB/s]
quantization.py: 100%|█████████████████████████████████████████████████████████████| 14.7k/14.7k [00:00<00:00, 51.6MB/s]
A new version of the following files was downloaded from https://huggingface.co/THUDM/chatglm3-6b:
- quantization.py
. Make sure to double-check they do not contain any added malicious code. To avoid downloading new versions of the code file, you can pin a revision.
A new version of the following files was downloaded from https://huggingface.co/THUDM/chatglm3-6b:
- modeling_chatglm.py
- quantization.py
. Make sure to double-check they do not contain any added malicious code. To avoid downloading new versions of the code file, you can pin a revision.
model.safetensors.index.json: 100%|████████████████████████████████████████████████| 21.2k/21.2k [00:00<00:00, 7.74MB/s]
model-00001-of-00007.safetensors: 100%|████████████████████████████████████████████| 1.83G/1.83G [15:17<00:00, 1.99MB/s]
Downloading shards:  14%|████████▊                                                     | 1/7 [15:17<1:31:44, 917.50s/itError while downloading from https://cdn-lfs-us-1.huggingface.co/repos/01/5a/015a4eda6314fbcdb0aecc00e73f604e0f398b10ef843cf3e7bfcf8d0b9c1d7d/f88d7f69a3940711b87308eb20dd0544df22aff81134fa0d5160d3c859f5d321?response-content-disposition=attachment%3B+filename*%3DUTF-8%27%27model-00002-of-00007.safetensors%3B+filename%3D%22model-00002-of-00007.safetensors%22%3B&Expires=1707015811&Policy=eyJTdGF0ZW1lbnQiOlt7IkNvbmRpdGlvbiI6eyJEYXRlTGVzc1RoYW4iOnsiQVdTOkVwb2NoVGltZSI6MTcwNzAxNTgxMX19LCJSZXNvdXJjZSI6Imh0dHBzOi8vY2RuLWxmcy11cy0xLmh1Z2dpbmdmYWNlLmNvL3JlcG9zLzAxLzVhLzAxNWE0ZWRhNjMxNGZiY2RiMGFlY2MwMGU3M2Y2MDRlMGYzOThiMTBlZjg0M2NmM2U3YmZjZjhkMGI5YzFkN2QvZjg4ZDdmNjlhMzk0MDcxMWI4NzMwOGViMjBkZDA1NDRkZjIyYWZmODExMzRmYTBkNTE2MGQzYzg1OWY1ZDMyMT9yZXNwb25zZS1jb250ZW50LWRpc3Bvc2l0aW9uPSoifV19&Signature=WrIM24-FutGC5aTXW55Ff4g-z5MO8K2NsIFjc7eRvXokY7fdHy4AdMQnVafWlpLWzEFBAosLvPSlR4VpXBUqBR%7EzSJZ7MEMqX6mT32Rj0eX0x8CfTVPUsOFu2T0nM1MNb0B7BYjDirjkjm2LUNnligb9znWwxYlchj6wEVV3I2UHh3IwmLdcUujmXiq9t07ZIzJ3tf39DEgRbjDgufdOHUO-gHQ%7Eb6bGWYhGRjpAog2U6P9CrzGNwIEIz6a6muh-raFzOukyi8Wxz2sys-HNprB5F1nsjahI3YhFLb6M6XyxWCFTCbPtTI8Yi24glkKArXD%7EZnyFcmZnNtGsnplEQg__&Key-Pair-Id=KCD77M1F0VK2B: HTTPSConnectionPool(host='cdn-lfs-us-1.huggingface.co', port=443): Read timed out.
Trying to resume download...
model-00002-of-00007.safetensors: 100%|████████████████████████████████████████████| 1.97G/1.97G [09:01<00:00, 3.21MB/s]
model-00002-of-00007.safetensors:  12%|█████▏                                      | 231M/1.97G [11:06<1:23:42, 346kB/s]
model-00003-of-00007.safetensors: 100%|████████████████████████████████████████████| 1.93G/1.93G [09:47<00:00, 3.28MB/s]
Downloading shards:  43%|███████████████████████████▍                                    | 3/7 [36:13<45:49, 687.47s/it]
model-00004-of-00007.safetensors:  42%|██████████████████▋                          | 755M/1.82G [04:13<05:18, 3.33MB/s]
model-00004-of-00007.safetensors: 100%|████████████████████████████████████████████| 1.82G/1.82G [09:31<00:00, 3.17MB/s]
model-00005-of-00007.safetensors: 100%|████████████████████████████████████████████| 1.97G/1.97G [10:47<00:00, 3.04MB/s]
model-00006-of-00007.safetensors: 100%|████████████████████████████████████████████| 1.93G/1.93G [09:40<00:00, 3.32MB/s]
model-00007-of-00007.safetensors: 100%|████████████████████████████████████████████| 1.05G/1.05G [05:37<00:00, 3.12MB/s]
Downloading shards: 100%|██████████████████████████████████████████████████████████████| 7/7 [1:11:55<00:00, 616.55s/it]
Loading checkpoint shards: 100%|██████████████████████████████████████████████████████████| 7/7 [00:20<00:00,  2.88s/it]
WARNING:root:Some parameters are on the meta device device because they were offloaded to the disk.

正常启动后，会自动使用浏览器打开 http://localhost:8501，然后就可以正常通过浏览器和大模型交互了，受限于硬件水平，响应非常慢。

四、运行情况

交互界面，注意红色内存报警，截图时已结束大模型进程，太慢了
交互界面，注意红色内存报警，截图时已结束大模型进程，太慢了
响应问题时，16G 的内存，使用量超过12G，GPU 功率10W 左右，可能 GPU 显存太小，没用起来
响应问题时，16G 的内存，使用量超过12G，GPU 功率10W 左右，可能 GPU 显存太小，没用起来

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