Mistral CoreML
| Property | Value |
|---|---|
| Author | Apple |
| Model Size | 7B parameters |
| Precision Options | FP16 & Int4 |
| Platform Requirement | macOS Sequoia (15) Beta |
What is mistral-coreml?
Mistral CoreML is Apple's optimized implementation of Mistral-7B-Instruct v0.3, specifically designed for Apple silicon devices. This conversion enables efficient deployment of the powerful Mistral language model within the Apple ecosystem, offering both FP16 and Int4 precision variants for different performance needs.
Implementation Details
The model represents a significant advancement in bringing large language models to Apple devices, leveraging CoreML's capabilities for optimal performance. The implementation includes support for the v3 Tokenizer and extends the vocabulary to 32,768 tokens, making it more versatile for various applications.
- Extended vocabulary (32,768 tokens)
- V3 Tokenizer support
- Function calling capabilities
- Available in both FP16 and Int4 precision
Core Capabilities
- Instruction-following and task completion
- Function calling support for structured outputs
- Optimized performance on Apple silicon
- Flexible deployment options with different precision levels
Frequently Asked Questions
Q: What makes this model unique?
This model uniquely combines the capabilities of Mistral-7B-Instruct with CoreML optimization, making it specifically designed for efficient execution on Apple silicon. The availability of both FP16 and Int4 versions allows developers to choose between higher accuracy or better performance based on their needs.
Q: What are the recommended use cases?
The model is ideal for iOS and macOS applications requiring on-device language processing, including chatbots, text generation, and function calling scenarios. It's particularly suited for applications where privacy and offline processing are priorities.
