shadowml/Daredevil-7B
Daredevil-7B is a 7 billion parameter language model created by shadowml, built upon the Mistral-7B-v0.1 architecture. This model is a merge of SamirGPT-v1, Slerp-CM-mist-dpo, and Mistral-7B-Merge-14-v0.2, utilizing the dare_ties merge method. It achieves an average score of 73.36 on the Open LLM Leaderboard, demonstrating strong performance across various reasoning and language understanding tasks. Daredevil-7B is suitable for general-purpose text generation and conversational AI applications.
Loading preview...
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.