OpenHermes-2.5-Mistral-7B-BOLA-Karate-Fine-Tuned-GGUF
| Property | Value |
|---|---|
| Parameter Count | 7.24B |
| License | Apache 2.0 |
| Model Type | Conversational AI |
| Base Model | EmilMarian/OpenHermes-2.5-Mistral-7B-BOLA-Karate-Fine-Tuned |
What is OpenHermes-2.5-Mistral-7B-BOLA-Karate-Fine-Tuned-GGUF?
This is a specialized quantized version of the OpenHermes 2.5 Mistral model, specifically fine-tuned for BOLA Karate applications. The model offers multiple GGUF quantization variants, allowing users to choose between different performance and quality trade-offs based on their specific needs.
Implementation Details
The model provides various quantization options ranging from 2.8GB to 14.6GB in size, each optimized for different use cases. Notable variants include the recommended Q4_K_S and Q4_K_M formats, which offer a good balance of speed and quality, and the Q8_0 format for highest quality output.
- Multiple quantization options (Q2_K through Q8_0)
- Size ranges from 2.8GB to 14.6GB
- Optimized for different hardware configurations
- Includes IQ-quant variants for enhanced performance
Core Capabilities
- Efficient deployment with various GGUF quantization options
- Optimized for both CPU and ARM architectures
- Balanced trade-offs between model size and performance
- Specialized fine-tuning for BOLA Karate domain
Frequently Asked Questions
Q: What makes this model unique?
This model stands out for its specialized quantization options and optimization for BOLA Karate applications, offering various compression levels while maintaining performance integrity.
Q: What are the recommended use cases?
For general use, the Q4_K_S (4.2GB) or Q4_K_M (4.5GB) variants are recommended for their optimal balance of speed and quality. For highest quality requirements, the Q8_0 variant (7.8GB) is suggested.
