Qwen2.5-14B-Arcee_base-i1-GGUF
| Property | Value |
|---|---|
| Base Model | Qwen2.5-14B-Arcee_base |
| Author | mradermacher |
| Model Format | GGUF with imatrix quantization |
| Size Range | 3.7GB - 12.2GB |
| Source | Hugging Face Repository |
What is Qwen2.5-14B-Arcee_base-i1-GGUF?
This is a quantized version of the Qwen2.5-14B-Arcee base model, offering various compression levels using GGUF format with imatrix quantization. The model provides multiple quantization options ranging from highly compressed (3.7GB) to high-quality (12.2GB) versions, allowing users to choose based on their hardware constraints and quality requirements.
Implementation Details
The model implements advanced quantization techniques including IQ (imatrix) quantization methods. It offers various quantization levels from IQ1 to Q6_K, each optimized for different use cases.
- Multiple quantization options (IQ1_S through Q6_K)
- Size ranges from 3.7GB to 12.2GB
- Optimized performance/size trade-offs
- imatrix quantization for improved quality at lower sizes
Core Capabilities
- Flexible deployment options for different hardware configurations
- Optimal size/speed/quality balance in Q4_K_S and Q4_K_M variants
- Enhanced performance through imatrix quantization
- Compatible with standard GGUF loading systems
Frequently Asked Questions
Q: What makes this model unique?
This model stands out for its comprehensive range of quantization options using imatrix technology, providing users with flexible choices between model size and performance. The IQ-quants are often preferable over similar-sized non-IQ quants for better quality.
Q: What are the recommended use cases?
For optimal performance, the Q4_K_M variant (9.1GB) is recommended as it provides a good balance of speed and quality. For resource-constrained environments, IQ3_S (6.8GB) offers better quality than standard Q3_K variants.
