Overview

liminerity/Neurotic-Jomainotrik-7b-slerp is a 7 billion parameter language model developed by liminerity. It is a product of merging two distinct models, liminerity/merge and bardsai/jaskier-7b-dpo-v5.6, utilizing the slerp (spherical linear interpolation) merge method via mergekit. This merging technique aims to combine the strengths of its constituent models, resulting in a versatile and capable LLM.

Key Capabilities & Performance

This model has been evaluated on the Open LLM Leaderboard and demonstrates strong performance across various benchmarks, achieving an average score of 76.40. Specific benchmark results include:

• AI2 Reasoning Challenge (25-Shot): 72.95
• HellaSwag (10-Shot): 89.15
• MMLU (5-Shot): 64.28
• TruthfulQA (0-shot): 77.64
• Winogrande (5-shot): 85.40
• GSM8k (5-shot): 68.99

These scores indicate its proficiency in tasks ranging from common sense reasoning and factual recall to mathematical problem-solving.

When to Use This Model

Given its balanced performance across multiple reasoning and language understanding benchmarks, Neurotic-Jomainotrik-7b-slerp is a strong candidate for general-purpose applications where a 7B parameter model is suitable. Its robust scores on tasks like HellaSwag and Winogrande suggest it excels in scenarios requiring strong common sense and contextual understanding.