docs/README_WINDOWS.md

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/releases/download/wheels/bitsandbytes-0.40.1.post1-py3-none-win_amd64.whl
    

11. Install optional document Q/A dependencies

    pip install -r reqs_optional/requirements_optional_langchain.txt
    pip install -r reqs_optional/requirements_optional_gpt4all.txt
    pip install -r reqs_optional/requirements_optional_langchain.gpllike.txt
    pip install -r reqs_optional/requirements_optional_langchain.urls.txt
    

    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.