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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](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`.
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