Qwen2.5-14B-YOYO-V4-i1-GGUF
| Property | Value |
|---|---|
| Author | mradermacher |
| Base Model | YOYO-AI/Qwen2.5-14B-YOYO-V4 |
| Model Type | Quantized GGUF |
| Size Range | 3.7GB - 12.2GB |
What is Qwen2.5-14B-YOYO-V4-i1-GGUF?
This is a specialized quantized version of the Qwen2.5-14B-YOYO-V4 model, optimized for efficiency and reduced size while maintaining performance. It uses advanced imatrix quantization techniques to offer various compression levels suitable for different hardware configurations and use cases.
Implementation Details
The model provides multiple quantization options, ranging from highly compressed IQ1_S (3.7GB) to high-quality Q6_K (12.2GB) variants. It implements innovative imatrix quantization (IQ) methods that often outperform traditional quantization approaches at similar sizes.
- Features weighted/imatrix quantization for optimal performance
- Offers 23 different quantization variants for flexibility
- Includes both IQ (imatrix) and standard quantization options
- Optimized for various size/quality trade-offs
Core Capabilities
- Highly efficient compression while maintaining model quality
- Compatible with standard GGUF file format
- Flexible deployment options from 3.7GB to 12.2GB
- Recommended Q4_K_M variant for optimal speed/quality balance
Frequently Asked Questions
Q: What makes this model unique?
This model stands out for its implementation of imatrix quantization, offering superior performance compared to traditional quantization methods at similar file sizes. It provides an extensive range of compression options to suit various hardware constraints and use cases.
Q: What are the recommended use cases?
For optimal performance, the Q4_K_M (9.1GB) variant is recommended as it offers a good balance of speed and quality. For resource-constrained environments, the IQ3 series provides good performance at smaller sizes, while Q6_K (12.2GB) is ideal for maximum quality.
