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Explore Mistral AI's extensive collection of models. Learn to select, prompt, and integrate Mistral's open-source and commercial models for tasks like classification, coding, and Retrieval Augmented Generation (RAG).

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🔍 Dive into the world of Mistral AI with the "Getting Started with Mistral" course! This course will walk you through accessing and utilizing Mistral's collection of open-source and commercial models for various tasks.

Course Summary

In this course, you'll explore Mistral AI's diverse collection of open-source and commercial models, including the Mixtral 8x7B and Mixtral 8x22B models. Here's what you'll learn:

  1. 🧩 Model Selection: Understand how to select the right Mistral model based on task complexity and speed requirements.
  2. 🛠️ Effective Prompting Techniques: Learn to prompt Mistral models effectively for tasks ranging from simple classification to advanced coding.
  3. 📊 Function Calling: Utilize Mistral's native function calling to integrate traditional code functionalities with LLM capabilities.
  4. 🔄 Retrieval Augmented Generation (RAG): Build a basic RAG system from scratch, incorporating similarity search and embeddings.

Key Points

  • 🚀 Access Mistral's diverse range of open-source and commercial models, including the Mixtral 8x22B, via web interface and API calls.
  • 💻 Leverage Mistral's JSON mode to generate structured LLM responses, facilitating integration into larger software applications.
  • 🔄 Enhance LLM capabilities by calling user-defined Python functions through Mistral's API, enabling tasks like web searches and database retrieval.

About the Instructor

🌟 Sophia Yang is the Head of Developer Relations at Mistral AI, bringing her expertise to guide you through leveraging Mistral's cutting-edge models effectively.

🔗 Enroll in the course or learn more at deeplearning.ai.