Testing LLM models and tools to query my documents
List of free ML books: https://www.kdnuggets.com/2020/03/24-best-free-books-understand-machine-learning.html
- the latest version of WSL (Windows Subsystem for Linux)
- Conda as the Python environment manager: Miniconda or Anaconda
To run this project, follow these steps:
- Clone the project:
git clone https://github.com/matthiaskozubal/Chat_with_my_data.git- Navigate into the project directory:
cd Chat_with_my_data- Create and activate a Conda environment with Python.
conda create -n chat python=3.10
conda activate chat- Install Poetry, if you haven't already:
curl -sSL https://install.python-poetry.org | bash- Install the project dependencies:
poetry install- Download the sample data
wget -P data/pdfs/ https://hastie.su.domains/ISLRv2_website.pdf- Enter your OpenAI API key (from https://platform.openai.com/account/api-keys) to the .env file
echo "OPEN_API_KEY=your_OpenAI_API_key" > .env- a) Run the project demo file in wsl (within the conda virtual environment):
python demo.py- b) Run the Jupyter demo notebook included with this project in VS Code:
code demo.ipynbCtrl+Shift+P -> Select Interpreter -> Python 3.10.12 ('chat')
click `run all`
- LangChain Chat with Your Data (DeepLearning.ai)
- Llama Index 101 with Vector DBs and GPT 3.5 (James Briggs | YouTube)
- https://www.reddit.com/r/LocalLLaMA/comments/14niv66/using_an_llm_just_for_your_own_data/
- https://www.reddit.com/r/LocalLLaMA/
- ChatGPT
- LLaMa (Meta AI)
- https://www.reddit.com/r/LocalLLaMA/comments/11o6o3f/how_to_install_llama_8bit_and_4bit/
- https://discord.com/invite/Y8H8uUtxc3
- https://www.reddit.com/r/LocalLLaMA/wiki/models/
- https://www.reddit.com/r/LocalLLaMA/wiki/guide/
- https://ai.meta.com/llama/
- Llama 2 is available for free for research and commercial use.
- models (with link to HuggingFace, Meta form must be filled in first):
- LangChain
- LlaMaIndex