Rombos-LLM-V2.6-Qwen-14b-GGUF
| Property | Value |
|---|---|
| Parameter Count | 14.8B |
| Model Type | Text Generation |
| Quantization | Multiple GGUF variants |
| Author | bartowski |
What is Rombos-LLM-V2.6-Qwen-14b-GGUF?
This is a comprehensive collection of GGUF quantized versions of the Rombos-LLM-V2.6-Qwen-14b model, specifically optimized using llama.cpp's imatrix quantization. The model offers various compression levels ranging from 5GB to 29.55GB, making it adaptable to different hardware configurations and performance requirements.
Implementation Details
The model implements different quantization techniques, from full F16 precision to highly compressed IQ2 variants. Each version is carefully balanced between model size and performance, using advanced techniques like embed/output weight preservation in certain variants.
- Uses llama.cpp release b3901 for quantization
- Implements imatrix calibration for optimal compression
- Provides special ARM-optimized variants (Q4_0_X_X series)
- Supports various inference platforms including LM Studio
Core Capabilities
- Multiple compression options from Q8_0 to IQ2_S
- Optimized performance for different hardware setups
- Special variants for ARM processors
- Consistent prompt format support
- Flexible deployment options
Frequently Asked Questions
Q: What makes this model unique?
The model stands out for its comprehensive range of quantization options, allowing users to choose the perfect balance between model size and performance for their specific hardware constraints. The implementation of imatrix quantization and special optimizations for various architectures makes it highly versatile.
Q: What are the recommended use cases?
For maximum quality, the Q6_K_L or Q6_K variants are recommended. For balanced performance, Q4_K_M is suggested as the default choice. For systems with limited RAM, the IQ3 or IQ2 variants offer surprisingly usable performance at smaller sizes.
