Hugging Face Overview
Model Overview
shadowml/BeagSake-7B is a 7 billion parameter language model developed by shadowml. It is a merged model, combining the strengths of shadowml/BeagleSempra-7B and shadowml/WestBeagle-7B using the slerp (spherical linear interpolation) merge method via LazyMergekit. This approach allows for a blend of the characteristics of its constituent models.
Key Capabilities
BeagSake-7B demonstrates solid performance across various benchmarks, indicating strong general language understanding and reasoning. Key evaluation results from the Open LLM Leaderboard include:
- Average Score: 75.38
- AI2 Reasoning Challenge (25-Shot): 72.44
- HellaSwag (10-Shot): 88.39
- MMLU (5-Shot): 65.23
- TruthfulQA (0-shot): 72.27
- Winogrande (5-shot): 82.16
- GSM8k (5-shot): 71.80
These scores suggest proficiency in common sense reasoning, factual recall, and mathematical problem-solving.
Good For
- General-purpose text generation: Creating coherent and contextually relevant text.
- Question Answering: Responding to queries based on its training data.
- Reasoning tasks: Handling tasks that require logical inference and problem-solving, as indicated by its AI2 Reasoning Challenge and GSM8k scores.