Jarvis is an AI-powered chatbot that uses the Orca Model for natural language processing tasks. This project is built with Chainlit and ctransformers to handle conversational AI and stream responses. Jarvis can answer user questions while keeping track of the conversation history, making interactions more dynamic and intelligent.
The model used in this project is Orca Mini 3B, a pre-trained causal language model hosted on Hugging Face.
- Conversational AI: Handles user inputs and provides context-aware responses.
- Streaming Responses: Utilizes Chainlit for streaming responses in real-time.
- Customizable: You can easily modify the prompt or model to suit your own needs.
- Orca Model Card: Orca Mini 3B on Hugging Face
- Open Orca Dataset: Open Orca Dataset on Hugging Face
- Chainlit Docs: Get Started with Chainlit
- Streamlit: Streamlit Official Website
- Python 3.8+
ctransformerslibrarychainlitlibrary
To get started, you’ll need to install the required dependencies.
pip install ctransformers chainlit
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# The Local LLM Crash Course - Build Your Own GPT in 2 hours!
This is the courseware and Codespace for the [The Local LLM Crash Course - Build Your Own GPT in 2 hours](https://www.udemy.com/course/the-local-llm-crash-course-build-a-hugging-face-ai-chatbot/?referralCode=EAD6017AA0001257DD9A)! Have fun with the course and use the Q&A if you run into any issues!
# Course Resources
### Codespaces Pricing and Free Credits
https://docs.github.com/en/billing/managing-billing-for-github-codespaces/about-billing-for-github-codespaces
### Hugging Face
* The Orca Model's Model Card: https://huggingface.co/zoltanctoth/orca_mini_3B-GGUF
### Installing `ctransformers` and Chainlit
Just for reference. Remember, you don't need to do this as it's pre-installed in your Codespace.pip install ctransformers chainlit
## The Open Orca Dataset
The dataset on Hugging Face: https://huggingface.co/datasets/Open-Orca/OpenOrca
## Chainlit and Streamlit
* Chainlit: https://docs.chainlit.io/get-started/overview
* Streamlit: https://streamlit.io/
## LangChain
### Installation
pip install langchain langchain-community
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