Rombos-LLM-V2.5-Qwen-14b
| Property | Value |
|---|---|
| Author | rombodawg |
| Parameter Count | 14 billion |
| Base Model | Qwen-2.5 |
| GGUF Version | Available |
| Model URL | Hugging Face |
What is Rombos-LLM-V2.5-Qwen-14b?
Rombos-LLM-V2.5-Qwen-14b is an advanced language model that represents a significant improvement over the original Qwen-2.5-14B through continuous fine-tuning. The model uniquely combines the instruct and base models using the Ties merge method, resulting in enhanced performance across various benchmarks.
Implementation Details
The model implements a novel approach to continuous fine-tuning, demonstrating the effectiveness of merging instruct and base model capabilities. Benchmark results show impressive performance, with notable scores in IFEval (58.40%) and BBH (49.39%).
- Continuous fine-tuning implementation using Ties merge method
- Available in GGUF format for efficient deployment
- Comprehensive benchmark evaluation across multiple tasks
Core Capabilities
- Strong performance in instruction-following tasks (IFEval: 58.40%)
- Robust reasoning capabilities (BBH: 49.39%)
- Professional knowledge evaluation (MMLU-PRO: 48.62%)
- Mathematical problem-solving (MATH Lvl 5: 15.63%)
- General question-answering (GPQA: 16.22%)
Frequently Asked Questions
Q: What makes this model unique?
The model's unique feature is its implementation of continuous fine-tuning and the successful merger of instruct and base models using the Ties merge method, resulting in superior performance compared to both original models.
Q: What are the recommended use cases?
Based on its benchmark performance, the model is particularly well-suited for instruction-following tasks, complex reasoning problems, and professional domain applications. It shows strong capabilities in both general-purpose and specialized tasks.
