### 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](https://sourceforge.net/projects/mingw/) and select, go to installation tab, then apply changes: * minigw32-base * mingw32-gcc-g++ 3. Download and install [Miniconda](https://docs.conda.io/projects/conda/en/latest/user-guide/install/windows.html) 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: ```bash 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: ```bash pip install -r requirements.txt ``` For GPU: ```bash pip install -r requirements.txt --extra-index-url https://download.pytorch.org/whl/cu118 ``` 10. For GPU, install bitsandbytes 4-bit and 8-bit: ```bash 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 ```bash 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 ```bash 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](https://github.com/UB-Mannheim/tesseract/wiki). 12. Install optional AutoGPTQ dependency: ```bash 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: ```bash 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: ```bash 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: ```bash 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](README_CPU.md) and [GPU](README_GPU.md) 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: ```bash (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`.