Josiefied-Qwen2.5-3B-Instruct-abliterated-v1-i1-GGUF
| Property | Value |
|---|---|
| Base Model | Qwen2.5-3B |
| Size Range | 1.0GB - 2.9GB |
| Author | mradermacher |
| Model Hub | Hugging Face |
What is Josiefied-Qwen2.5-3B-Instruct-abliterated-v1-i1-GGUF?
This is a highly optimized quantized version of the Qwen2.5-3B model, offering various compression formats using both imatrix and static quantization techniques. The model provides multiple variants optimized for different use cases, balancing size, speed, and quality.
Implementation Details
The implementation features multiple quantization types, from highly compressed IQ1_S (1.0GB) to high-quality Q6_K (2.9GB). The model utilizes advanced imatrix quantization methods alongside traditional static quantization approaches.
- Multiple compression options ranging from 1.0GB to 2.9GB
- Innovative imatrix quantization techniques for optimal performance
- Various quality-size tradeoffs to suit different requirements
- Optimized formats for different computational resources
Core Capabilities
- Flexible deployment options with multiple quantization variants
- Optimal balance between model size and performance
- Enhanced efficiency through imatrix quantization
- Support for resource-constrained environments
Frequently Asked Questions
Q: What makes this model unique?
The model offers an extensive range of quantization options, particularly notable for its imatrix quantization variants that often outperform traditional quantization methods at similar sizes. The Q4_K_M variant is specifically recommended for optimal speed-quality balance.
Q: What are the recommended use cases?
For optimal performance, the Q4_K_M (2.2GB) variant is recommended as it provides a good balance of speed and quality. For resource-constrained environments, the IQ3 variants offer reasonable performance at smaller sizes. The Q6_K variant is suitable for scenarios requiring maximum quality.
