Q-bert/Optimus-7B
Optimus-7B is a 7 billion parameter language model developed by Q-bert, fine-tuned from Mistral-7B-v0.1. This model specializes in mathematical reasoning, having been trained on the MetaMathQA dataset. It demonstrates strong performance across various benchmarks, including an average score of 69.09 on the Open LLM Leaderboard, making it suitable for tasks requiring robust logical and quantitative understanding.
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Optimus-7B: A Math-Optimized Language Model
Optimus-7B is a 7 billion parameter language model developed by Q-bert, built upon the Mistral-7B-v0.1 architecture. Its primary differentiation lies in its fine-tuning on the MetaMathQA dataset, which specifically enhances its capabilities in mathematical reasoning and problem-solving.
Key Capabilities & Performance
This model has been evaluated on the Open LLM Leaderboard and achieves a competitive average score of 69.09. Notable benchmark results include:
- ARC (25-shot): 65.44
- HellaSwag (10-shot): 85.41
- MMLU (5-shot): 63.61
- TruthfulQA (0-shot): 55.79
- Winogrande (5-shot): 78.77
- GSM8K (5-shot): 65.50 (specifically for mathematical word problems)
Use Cases
Optimus-7B is particularly well-suited for applications requiring strong quantitative and logical reasoning. Developers can leverage this model for:
- Mathematical problem-solving: Generating solutions or explanations for math-related queries.
- Data analysis and interpretation: Assisting with tasks that involve numerical understanding.
- Educational tools: Creating interactive math tutors or content generation for STEM fields.
The model supports the ChatML format for interaction.