Useful Command and Links:
python3 -m venv .venv source .venv/bin/activate which python python3 -m pip install --upgrade pip
- model_path = https://huggingface.co/TheBloke/Mistral-7B-Instruct-v0.1-GGUF
- Kaggle Datatset link = https://www.kaggle.com/datasets/harshsinghal/nlp-and-llm-related-arxiv-papers
- Embedding Model: https://huggingface.co/BAAI/bge-base-en-v1.5
- Hugging Face(ChatInterface) -> https://www.gradio.app/docs/chatinterface
Steps:
- Creating a virtual environment managing the dependencies.
- what .env file and and how to load secrets from .env file
- how to configure and load llm models from local folder and using together api
- how to modularize your code and create a vectore DB
- Pydantic & What is fast api from concepts to code
- What is gradio and how to create UIs using Gradio
- Combine everything and create a fully functional LLM App.
YouTube Playlist Link: https://youtube.com/playlist?list=PLOrU905yPYXIqQLY6ulQqB8e414-DFuyd&si=nStqjRUsbytX3J5k