Model Overview

kuno-royale-7B is a 7 billion parameter language model developed by core-3. It is a merged model, combining the strengths of two base models: SanjiWatsuki/Kunoichi-DPO-v2-7B and eren23/ogno-monarch-jaskier-merge-7b. The merge was performed using LazyMergekit, employing an slerp merge method with specific parameter weighting for self-attention and MLP layers.

Performance Highlights

kuno-royale-7B exhibits strong benchmark performance, achieving an average score of 74.74 across a suite of evaluations. Key scores include:

• MMLU: 65.13
• HellaSwag: 88.20
• GSM8K: 69.90

These scores position it competitively against its constituent models and other 7B-class models like SanjiWatsuki/Kunoichi-DPO-v2-7B, often slightly outperforming them in several categories. However, the developers note that a newer version, core-3/kuno-royale-v2-7b, is likely to offer improved performance.

Intended Use Cases

This model is suitable for a range of general-purpose natural language processing tasks, including:

• Text generation
• Question answering
• Reasoning tasks
• Conversational AI

Its balanced performance across various benchmarks suggests its utility in applications requiring robust language understanding and generation capabilities.