DeepSeek-R1-Distill-Qwen-7B-TIR-o3-mini-code-GGUF
| Property | Value |
|---|---|
| Base Model | DeepSeek-R1-Distill-Qwen-7B |
| Format | GGUF |
| Author | mradermacher |
| Model URL | Hugging Face |
What is DeepSeek-R1-Distill-Qwen-7B-TIR-o3-mini-code-GGUF?
This is a quantized version of the DeepSeek-R1-Distill-Qwen-7B model, specifically optimized for code-related tasks. The model offers various quantization options to balance between model size and performance, ranging from 3.1GB to 15.3GB.
Implementation Details
The model provides multiple quantization variants optimized for different use cases:
- Q2_K (3.1GB) - Smallest size option
- Q4_K_S/M (4.6-4.8GB) - Recommended for balanced performance
- Q6_K (6.4GB) - Very good quality option
- Q8_0 (8.2GB) - Highest quality with reasonable size
- F16 (15.3GB) - Full precision, maximum quality
Core Capabilities
- Code generation and understanding
- Multiple quantization options for different hardware requirements
- Optimized performance with Q4_K variants
- Flexible deployment options from 3.1GB to 15.3GB
Frequently Asked Questions
Q: What makes this model unique?
This model offers a wide range of quantization options while maintaining code-specific capabilities, making it highly versatile for different deployment scenarios and hardware constraints.
Q: What are the recommended use cases?
The model is best suited for code-related tasks, with the Q4_K_S and Q4_K_M variants recommended for most users as they offer the best balance between size and performance.
