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Getting Started with Mistral

Welcome to the repository for the course Getting Started with Mistral by DeepLearning.AI.

About the Course

In this course, you’ll access Mistral AI’s collection of open-source and commercial models, including the Mixtral 8x7B model and the latest Mixtral 8x22B. You’ll learn about selecting the right model for your use case and get hands-on with features like effective prompting techniques, function calling, JSON mode, and Retrieval Augmented Generation (RAG).

Key Topics Covered

  1. Model Selection

    • Access and prompt Mistral models via API calls.
    • Decide on the complexity of tasks:
      • Simple: Classification
      • Medium: Email writing
      • Advanced: Coding
    • Consider speed requirements to choose the appropriate model.

  2. Function Calling

    • Learn to use Mistral’s native function calling.
    • Enable LLMs to perform tasks better suited for traditional code, such as querying databases for numerical data.

  3. Retrieval Augmented Generation (RAG)

    • Build a basic RAG system from scratch with similarity search.
    • Properly chunk data, create embeddings, and implement RAG as a function in your chat system.

  4. Interactive Chat Interface

    • Build a chat interface to interact with Mistral models.
    • Ask questions about a document you upload.

Course Objectives

By the end of this course, you’ll be equipped to:

  • Effectively leverage Mistral AI’s open-source and commercial models.
  • Build scalable and efficient systems for various use cases.
  • Implement advanced techniques like RAG and function calling.

Getting Started

  1. Clone the repository: 
    git clone https://github.com/RuvenGuna94/Getting-started-with-Mistral.git
cd Getting-started-with-Mistral
  2. Follow the provided notebooks to explore Mistral AI's capabilities.

Additional Resources

License

This repository is provided for educational purposes.

Happy learning!