DeepSeek-R1-Distill-Qwen-14B-abliterated-v2-GGUF
| Property | Value |
|---|---|
| Author | mradermacher |
| Base Model | DeepSeek-R1-Distill-Qwen-14B |
| Format | GGUF |
| Size Range | 5.9GB - 15.8GB |
What is DeepSeek-R1-Distill-Qwen-14B-abliterated-v2-GGUF?
This is a quantized version of the DeepSeek-R1-Distill-Qwen-14B model, optimized for efficient deployment through GGUF format. It offers multiple quantization options ranging from Q2_K to Q8_0, allowing users to balance between model size and performance based on their specific needs.
Implementation Details
The model provides various quantization levels with different size-quality trade-offs:
- Q2_K: 5.9GB - Smallest size option
- Q4_K_S/M: 8.7-9.1GB - Fast and recommended for general use
- Q6_K: 12.2GB - Very good quality
- Q8_0: 15.8GB - Highest quality, fast performance
Core Capabilities
- Multiple quantization options for different deployment scenarios
- Optimized performance with GGUF format
- Size-efficient compression while maintaining quality
- Support for both standard and IQ-based quantization methods
Frequently Asked Questions
Q: What makes this model unique?
This model stands out for its variety of quantization options and optimized GGUF format, making it highly versatile for different deployment scenarios. The availability of both standard and IQ-based quantization provides users with extensive flexibility in choosing the right balance between model size and performance.
Q: What are the recommended use cases?
For general use, the Q4_K_S and Q4_K_M variants (8.7-9.1GB) are recommended due to their good balance of speed and quality. For highest quality requirements, the Q8_0 variant (15.8GB) is advised, while resource-constrained environments might benefit from the smaller Q2_K or Q3_K variants.
