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README_WINDOWS.md

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Windows 10/11

Follow these steps:

  1. Install Visual Studio 2022 (requires newer windows versions of 10/11) with following selected:

    • Windows 11 SDK
    • C++ Universal Windows Platform support for development
    • MSVC VS 2022 C++ x64/x86 build tools
    • C++ CMake tools for Windows

  2. Download the MinGW installer from the MinGW website and select, go to installation tab, then apply changes:

    • minigw32-base
    • mingw32-gcc-g++

  3. Download and install Miniconda and Run Miniconda shell (not power shell) as administrator

  4. Run: set path=%path%;c:\MinGW\msys\1.0\bin\ to get C++ in path

  5. Download latest nvidia driver for windows

  6. Confirm can run nvidia-smi and see driver version

  7. Run: wsl --install

  8. Setup Conda Environment:

     conda create -n h2ogpt -y
 conda activate h2ogpt
 conda install python=3.10 -c conda-forge -y
 conda install cudatoolkit -c conda-forge -y  # required for bitsandbytes
 python --version  # should say python 3.10.xx
 python -c "import os, sys ; print('hello world')"  # should print "hello world"
 git clone https://github.com/h2oai/h2ogpt.git
 cd h2ogpt

  9. Install dependencies.

    For CPU:

    pip install -r requirements.txt

    For GPU:

    pip install -r requirements.txt --extra-index-url https://download.pytorch.org/whl/cu118

  10. For GPU, install bitsandbytes 4-bit and 8-bit:

    pip uninstall bitsandbytes
pip install https://github.com/jllllll/bitsandbytes-windows-webui/raw/main/bitsandbytes-0.39.0-py3-none-any.whl

    unless you have compute capability <7.0, then your GPU only supports 8-bit (not 4-bit) and you should install older bitsandbytes:

    pip uninstall bitsandbytes
pip install https://github.com/jllllll/bitsandbytes-windows-webui/raw/main/bitsandbytes-0.38.1-py3-none-any.whl

  11. Install optional document Q/A dependencies

    for fil in reqs_optional/requirements_optional_langchain.txt reqs_optional/requirements_optional_gpt4all.txt reqs_optional/requirements_optional_langchain.gpllike.txt reqs_optional/requirements_optional_langchain.urls.txt ; do pip install -r $fil --extra-index-url https://download.pytorch.org/whl/cu118 ; done

    Optional dependencies for supporting unstructured package

    python -m nltk.downloader all

    For supporting Word and Excel documents download and install libreoffice: https://www.libreoffice.org/download/download-libreoffice/ . To support OCR, downnload and install tesseract.

  12. Install optional AutoGPTQ dependency:

    pip install -r https://github.com/PanQiWei/AutoGPTQ/releases/download/v0.2.2/auto_gptq-0.2.2+cu118-cp310-cp310-win_amd64.whl

  13. Run h2oGPT for chat only:

    python generate.py --base_model=h2oai/h2ogpt-gm-oasst1-en-2048-open-llama-7b --score_model=None

    For document Q/A with UI using CPU:

    python generate.py --base_model='llama' --prompt_type=wizard2 --score_model=None --langchain_mode='UserData' --user_path=user_path

    For document Q/A with UI using GPU:

    python generate.py --base_model=h2oai/h2ogpt-gm-oasst1-en-2048-open-llama-7b --langchain_mode=MyData --score_model=None

For the above, ignore the CLI output saying 0.0.0.0, and instead point browser at http://localhost:7860 (for windows/mac) or the public live URL printed by the server (disable shared link with --share=False).

See CPU and GPU for some other general aspects about using h2oGPT on CPU or GPU, such as which models to try.

When running windows on GPUs with bitsandbytes you should see something like:

(h2ogpt) c:\Users\pseud\h2ogpt>python generate.py --base_model=h2oai/h2ogpt-oig-oasst1-512-6_9b --load_8bit=True
bin C:\Users\pseud\.conda\envs\h2ogpt\lib\site-packages\bitsandbytes\libbitsandbytes_cuda118.dll
Using Model h2oai/h2ogpt-oig-oasst1-512-6_9b
device_map: {'': 0}
Loading checkpoint shards: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 3/3 [00:06<00:00,  2.16s/it]
device_map: {'': 1}
Running on local URL:  http://0.0.0.0:7860
Running on public URL: https://f8fa95f123416c72dc.gradio.live

This share link expires in 72 hours. For free permanent hosting and GPU upgrades (NEW!), check out Spaces: https://huggingface.co/spaces

where bitsandbytes cuda118 was used because conda cuda toolkit is cuda 11.8. You can confirm GPU use via nvidia-smi showing GPU memory consumed.

Note 8-bit inference is about twice slower than 16-bit inference, and the only use of 8-bit is to keep memory profile low.

Bitsandbytes can be uninstalled (pip uninstall bitsandbytes) and still h2oGPT can be used if one does not pass --load_8bit=True.