Daredevil-7B: A Merged 7B Language Model

Daredevil-7B, developed by shadowml, is a 7 billion parameter language model based on the Mistral-7B-v0.1 architecture. It is a product of a sophisticated merge using the dare_ties method, combining the strengths of three distinct models: SamirGPT-v1, abacusai/Slerp-CM-mist-dpo, and EmbeddedLLM/Mistral-7B-Merge-14-v0.2.

Key Capabilities & Performance

This model demonstrates robust performance across a range of benchmarks, as evaluated on the Open LLM Leaderboard:

• Average Score: 73.36
• AI2 Reasoning Challenge (25-Shot): 69.37
• HellaSwag (10-Shot): 87.17
• MMLU (5-Shot): 65.30
• TruthfulQA (0-shot): 64.09
• Winogrande (5-shot): 81.29
• GSM8k (5-shot): 72.93

These scores indicate its proficiency in reasoning, common sense, language understanding, and mathematical problem-solving.

Good For

• General-purpose text generation and completion tasks.
• Applications requiring strong reasoning and language comprehension.
• Developers looking for a capable 7B model with a balanced performance profile.