DeepSeek-R1-ReDistill-Qwen-7B-v1.1-Q8_0-GGUF
| Property | Value |
|---|---|
| Parameter Count | 7 Billion |
| Model Type | Language Model |
| Format | GGUF (Quantized 8-bit) |
| Original Source | mobiuslabsgmbh/DeepSeek-R1-ReDistill-Qwen-7B-v1.1 |
| Repository | Hugging Face |
What is DeepSeek-R1-ReDistill-Qwen-7B-v1.1-Q8_0-GGUF?
This is a converted version of the DeepSeek-R1-ReDistill-Qwen model, optimized for local deployment using llama.cpp. The model has been quantized to 8-bit precision (Q8_0) to balance performance and resource requirements while maintaining good output quality.
Implementation Details
The model utilizes the GGUF format, which is specifically designed for efficient inference using llama.cpp. This implementation allows for both CLI and server deployment options, making it versatile for different use cases.
- Converted from original DeepSeek model using llama.cpp
- 8-bit quantization for optimal performance
- Supports context window of 2048 tokens
- Compatible with both CPU and GPU acceleration
Core Capabilities
- Local deployment through llama.cpp
- Efficient inference with reduced memory footprint
- Support for both CLI and server implementations
- Cross-platform compatibility (Linux, MacOS)
Frequently Asked Questions
Q: What makes this model unique?
This model stands out for its efficient local deployment capabilities through the GGUF format and llama.cpp integration, making it accessible for users who need to run large language models locally with reasonable resource requirements.
Q: What are the recommended use cases?
The model is ideal for developers and researchers who need to run inference locally, whether for privacy concerns or deployment requirements. It's particularly suitable for applications requiring a balance between performance and resource usage.
