KangalKhan-RawRuby-7B Overview

KangalKhan-RawRuby-7B is a 7 billion parameter language model developed by Yuma42. It is a merged model, combining the capabilities of Yuma42/KangalKhan-Ruby-7B-Fixed and Yuma42/KangalKhan-RawEmerald-7B using the slerp merge method via LazyMergekit. This approach aims to synthesize the strengths of both base models into a single, cohesive unit.

Key Capabilities & Performance

The model demonstrates solid performance across a range of benchmarks, as evaluated on the Open LLM Leaderboard. Key metrics include:

• Average Score: 68.95 on the primary leaderboard.
• Reasoning: Achieves 66.89 on AI2 Reasoning Challenge (25-Shot) and 62.02 on GSM8k (5-shot).
• Common Sense: Scores 85.53 on HellaSwag (10-Shot) and 78.69 on Winogrande (5-shot).
• General Knowledge: MMLU (5-Shot) score of 63.46.

It supports a 4096-token context length and is designed to be used with a ChatML-like instruction format. GGUF quantized versions are available for efficient deployment.

Good For

• General-purpose text generation and understanding.
• Applications requiring reasoning and common sense capabilities.
• Developers looking for a merged model with balanced performance across various tasks.