| Property | Value |
|---|---|
| Parameter Count | 7.24B |
| License | CC-BY-NC-4.0 |
| Base Model | Alsebay/NarumashiRTS-7B-V2-1 |
| Language | English |
What is NarumashiRTS-7B-V2-1-GGUF?
NarumashiRTS-7B-V2-1-GGUF is a quantized version of the NarumashiRTS model, specifically designed for roleplay applications. Built on the Mistral architecture, this model offers various quantization options ranging from 2.8GB to 14.6GB, allowing users to balance between model size and performance according to their needs.
Implementation Details
The model implements multiple quantization techniques, including both standard and IQ (Improved Quantization) variants. Notable quantization options include Q2_K (2.8GB), IQ3_XS (3.1GB), up to Q8_0 (7.8GB) and f16 (14.6GB) versions.
- Multiple quantization options for different use-cases
- Improved Quantization (IQ) variants available
- Optimized for both performance and storage efficiency
- Compatible with text-generation-inference framework
Core Capabilities
- Specialized for roleplay applications
- Efficient text generation and processing
- Flexible deployment options with various quantization levels
- Optimized for different hardware configurations
Frequently Asked Questions
Q: What makes this model unique?
This model stands out for its variety of quantization options, particularly the IQ-quants which often provide better quality than similar-sized non-IQ variants. The Q4_K_S and Q4_K_M variants are specifically recommended for their balance of speed and quality.
Q: What are the recommended use cases?
The model is primarily designed for roleplay applications and text generation. For optimal performance, users with limited resources should consider the Q4_K variants, while those prioritizing quality can opt for Q6_K or Q8_0 versions.