Orca-2-7B-GGUF
| Property | Value |
|---|---|
| Parameter Count | 6.74B |
| Base Model | Microsoft/Orca-2-7b |
| License | Microsoft Research License |
| Paper | Orca 2 Paper |
What is Orca-2-7B-GGUF?
Orca-2-7B-GGUF is a quantized version of Microsoft's Orca-2 language model, optimized by TheBloke for efficient deployment across various computing environments. This model is particularly notable for its strong reasoning capabilities and has been converted to the GGUF format, which enables efficient inference on both CPU and GPU systems.
Implementation Details
The model comes in multiple quantization formats, ranging from 2-bit to 8-bit precision, offering different trade-offs between model size and performance. The Q4_K_M variant (4-bit quantization) is recommended for balanced performance, requiring only 4.08GB of storage and 6.58GB of RAM.
- Supports multiple quantization levels (Q2_K to Q8_0)
- Compatible with llama.cpp and various UI implementations
- Uses ChatML prompt format
- Optimized for both CPU and GPU inference
Core Capabilities
- Advanced reasoning over user-provided data
- Reading comprehension and analysis
- Mathematical problem solving
- Text summarization
- Single-turn response optimization
Frequently Asked Questions
Q: What makes this model unique?
This model stands out for its specialized training on reasoning tasks and its efficient GGUF format implementation, making it accessible for various deployment scenarios while maintaining strong performance on complex reasoning tasks.
Q: What are the recommended use cases?
The model is designed primarily for research purposes and excels in tasks requiring reasoning, data analysis, and structured problem-solving. It's particularly well-suited for academic and research applications where understanding complex relationships and logical reasoning are crucial.
