Explore Mistral’s three open source models (Mistral 7B, Mixtral 8x7B, and the latest Mixtral 8x22B), and three commercial models (small, medium, and large), which Mistral provides access to via web interface and API calls.
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Explore Mistral’s three open source models (Mistral 7B, Mixtral 8x7B, and the latest Mixtral 8x22B), and three commercial models (small, medium, and large), which Mistral provides access to via web interface and API calls.
Leverage Mistral’s JSON mode to generate LLM responses in a structured JSON format, enabling integration of LLM outputs into larger software applications.
Use Mistral’s API to call user-defined Python functions for tasks like web searches or retrieving text from databases, enhancing the LLM’s ability to find relevant information to answer user queries.
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).
In detail:
By the end of this course, you’ll be equipped to leverage Mistral AI’s leading open source and commercial models.
Getting Started with Mistral is a beginner-friendly course and it’s suitable for anyone who wants to learn about and use Mistral AI’s collection of advanced open source and commercial LLMs. If you have taken ChatGPT Prompt Engineering for Developers or Prompt Engineering with Llama 2, this is a great next step!
Introduction
Overview
Prompting
Model Selection
Function Calling
RAG from Scratch
Chatbot
Conclusion
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