Dolphin3.0-R1-Mistral-24B
| Property | Value |
|---|---|
| Base Model | Mistral 24B |
| Training Data | 800k reasoning traces |
| Recommended Temperature | 0.05-0.1 |
| Model URL | https://huggingface.co/cognitivecomputations/Dolphin3.0-R1-Mistral-24B |
What is Dolphin3.0-R1-Mistral-24B?
Dolphin3.0-R1-Mistral-24B represents the next generation of the Dolphin series, designed as an ultimate general-purpose local model. Built on the Mistral 24B architecture, it has been specifically trained for 3 epochs on 800,000 reasoning traces from the Dolphin-R1 dataset. This model stands out for its versatility in handling coding tasks, mathematical problems, agentic interactions, and function calling capabilities.
Implementation Details
The model utilizes the ChatML format for interactions and requires notably low temperature settings (0.05-0.1) for optimal performance. It can be deployed through various platforms including Ollama, LM Studio, and the Hugging Face Transformers library, with a particular focus on providing users complete control over the system prompt and alignment.
- Fully controllable system prompts for customized behavior
- ChatML template integration for structured conversations
- Local deployment options for data privacy
- Optimized performance at low temperature settings
Core Capabilities
- Advanced reasoning and structured thinking
- Coding assistance across multiple languages
- Mathematical problem-solving
- Function calling and API interactions
- General-purpose conversational abilities
Frequently Asked Questions
Q: What makes this model unique?
Unlike cloud-based alternatives, Dolphin3.0-R1 gives complete control to the system owner, allowing custom system prompts, alignment, and data handling. It's designed to be a tool that extends the user's capabilities without imposing external ethical constraints.
Q: What are the recommended use cases?
The model excels in coding tasks, mathematical reasoning, general conversational interactions, and function calling scenarios. It's particularly suitable for businesses seeking to integrate AI capabilities while maintaining control over their data and model behavior.
