Dolphin 2.7 Mixtral 8x7B GGUF
| Property | Value |
|---|---|
| Parameter Count | 46.7B |
| Model Type | Mixtral-based GGUF |
| License | Apache 2.0 |
| Context Length | 32K tokens |
What is dolphin-2.7-mixtral-8x7b-GGUF?
Dolphin 2.7 Mixtral is an advanced language model based on the Mixtral architecture, specifically optimized for coding and conversational tasks. This GGUF version offers various quantization options from 2-bit to 8-bit, allowing flexible deployment across different hardware configurations. The model was trained using 7 high-quality datasets including Dolphin, Airoboros, Magicoder, and OpenHermes.
Implementation Details
The model implements the ChatML prompt format and offers multiple quantization levels for different use cases. The Q4_K_M quantization (4-bit) is recommended for balanced performance, while Q5_K_M provides very low quality loss at the cost of larger size. The model supports GPU acceleration through various frameworks including llama.cpp.
- Multiple quantization options (2-bit to 8-bit)
- 32K context length support
- Comprehensive coding capabilities
- Enhanced conversational abilities
Core Capabilities
- Advanced code generation and understanding
- Natural conversational interactions
- Flexible deployment options
- High compliance and instruction following
- Support for multiple programming languages
Frequently Asked Questions
Q: What makes this model unique?
The model combines Mixtral's powerful architecture with specialized training on coding and conversational tasks, offering multiple quantization options for efficient deployment while maintaining high performance.
Q: What are the recommended use cases?
Primary use cases include code generation, technical documentation, conversational AI applications, and general-purpose text generation tasks. The model excels particularly in programming-related tasks.
