Qwen2.5-14B-Mixed-Instruct-GGUF
| Property | Value |
|---|---|
| Parameter Count | 14.8B |
| Model Type | Transformer-based Instruction Model |
| Base Model | ddh0/Qwen2.5-14B-Mixed-Instruct |
| Author | mradermacher |
What is Qwen2.5-14B-Mixed-Instruct-GGUF?
Qwen2.5-14B-Mixed-Instruct-GGUF is a quantized version of the Qwen2.5-14B model, specifically optimized for instruction-following tasks. This implementation provides various GGUF quantization options, allowing users to balance between model size and performance based on their specific needs.
Implementation Details
The model comes in multiple quantization variants, ranging from 5.9GB to 15.8GB in size. Notable implementations include Q4_K_S and Q4_K_M which are recommended for their optimal balance of speed and quality, while Q8_0 offers the highest quality at 15.8GB.
- Multiple quantization options (Q2_K through Q8_0)
- Size variants from 5.9GB to 15.8GB
- Optimized for both performance and efficiency
- Supports English language processing
Core Capabilities
- Instruction following and conversational tasks
- Efficient deployment with various memory footprints
- Optimized for different hardware configurations
- Fast inference on supported platforms
Frequently Asked Questions
Q: What makes this model unique?
The model offers a comprehensive range of quantization options, making it highly versatile for different deployment scenarios. The Q4_K variants are particularly notable for offering a good balance of speed and quality.
Q: What are the recommended use cases?
For most applications, the Q4_K_S or Q4_K_M variants (8.7GB and 9.1GB respectively) are recommended as they offer fast performance with good quality. For highest quality requirements, the Q8_0 variant (15.8GB) is recommended.
