Qwen2.5-14B-Instruct-Uncensored-Q4_K_M-GGUF
| Property | Value |
|---|---|
| Parameter Count | 14.8B |
| License | GPL-3.0 |
| Supported Languages | Chinese, English |
| Format | GGUF (Q4_K_M quantization) |
What is Qwen2.5-14B-Instruct-Uncensored-Q4_K_M-GGUF?
This is a quantized version of the Qwen2.5-14B-Instruct-Uncensored model, specifically optimized for deployment using llama.cpp. The model has been converted to the efficient GGUF format with Q4_K_M quantization, making it more accessible for local deployment while maintaining good performance.
Implementation Details
The model is built upon the base Qwen2.5-14B architecture and has been converted using llama.cpp through the GGUF-my-repo pipeline. It features Q4_K_M quantization, which offers an excellent balance between model size and performance.
- Optimized for llama.cpp deployment
- Q4_K_M quantization for efficient inference
- Supports both CLI and server deployment modes
- Compatible with standard llama.cpp installation methods
Core Capabilities
- Bilingual support for Chinese and English
- Uncensored instruction-following capabilities
- Efficient local deployment through llama.cpp
- Reduced memory footprint while maintaining model quality
Frequently Asked Questions
Q: What makes this model unique?
This model stands out for its efficient quantization while maintaining the capabilities of the original Qwen2.5-14B model, particularly its bilingual abilities and uncensored instruction-following capabilities. The Q4_K_M quantization makes it more accessible for local deployment.
Q: What are the recommended use cases?
The model is ideal for local deployment scenarios where efficient resource usage is important. It's particularly suited for bilingual applications requiring both Chinese and English language processing, and for use cases where uncensored model responses are needed.
