Mistral Large with Function Calling - Review and Code
AI Summary
- Mistral AI’s New Model Overview
- New model released by Mistral AI
- Not hyped, but acknowledged as a good model
- Not overly restricted by RLHF like some big companies
- Developed in under 10 months by a company less than a year old
- Open source 7 billion parameter base and fine-tuned instruct models
- Large proprietary models also released
- Cost-effective production at 20 million euros
- Company and Model Strategy
- Multiple iterations allow for learning and improvement
- Mistral AI’s large model also available on Azure
- Proprietary model served on Mistral’s servers
- Option for on-premises use, appealing to companies with sensitive data
- Model Capabilities and Performance
- Multimodal, supporting Western European languages
- 32k context window, with potential for future expansion
- Precise instruction following with customizable moderation policies
- Strong reasoning capabilities, performs well on benchmarks like GSM 8K
- Released alongside a chat platform called Le Chat
- Function Calling
- Mistral Large supports function calling, similar to OpenAI models
- Allows for integration with various tasks and tools
- Demonstrated with a hypothetical restaurant booking and ordering system
- Can handle multiple arguments and provide structured responses
- Testing and Usage
- Mistral Large and Mistral Medium models tested with various prompts
- Models show distinct output styles and good reasoning
- Encouraged to test models with personal prompts for comparison
- Function calling tested with a detailed example
- Conclusion
- Mistral Large is a competitive alternative to models from OpenAI and others
- Particularly strong in reasoning and function calling tasks
- Worth exploring for specific use cases
- Video Content
- Encourages likes, subscriptions, and comments
- Promises to read comments for the first 24-48 hours after video release