Dolphin 2.1 Mistral 7B GGUF
| Property | Value |
|---|---|
| Parameter Count | 7.24B |
| Model Type | Mistral |
| License | Apache 2.0 |
| Author | Eric Hartford (Quantized by TheBloke) |
What is dolphin-2.1-mistral-7B-GGUF?
Dolphin 2.1 Mistral 7B GGUF is a quantized version of the original Dolphin model, based on Microsoft's Orca approach and implemented on the Mistral architecture. This model is specifically designed for efficient deployment while maintaining high-quality AI assistance capabilities, featuring multiple quantization options from 2-bit to 8-bit precision to accommodate different hardware configurations and performance requirements.
Implementation Details
The model utilizes the GGUF format, which is the successor to GGML, providing improved efficiency and compatibility with modern LLM deployment tools. It was trained for 48 hours over 4 epochs on 4x A100s, incorporating both the Dolphin dataset and Jon Durbin's Airoboros dataset for enhanced creativity.
- Supports multiple quantization levels (Q2_K through Q8_0)
- Uses ChatML prompt format for consistent interaction
- Includes GPU acceleration support
- Compatible with various interfaces including llama.cpp, text-generation-webui, and more
Core Capabilities
- Uncensored responses with high compliance
- Enhanced creative generation
- Efficient resource utilization through quantization
- Extended context handling
- Flexible deployment options
Frequently Asked Questions
Q: What makes this model unique?
This model combines the efficiency of GGUF quantization with the powerful Mistral architecture, offering uncensored responses while maintaining high performance. It's particularly notable for its balance between resource efficiency and output quality.
Q: What are the recommended use cases?
The model is suitable for various applications requiring AI assistance, from creative writing to technical analysis. The multiple quantization options make it adaptable to different hardware configurations, from consumer laptops to high-end servers.
