Overview

Q-bert/MetaMath-Cybertron-Starling is a 7 billion parameter language model developed by Q-bert. It was created through a slerp merge of two distinct models: Q-bert/MetaMath-Cybertron and berkeley-nest/Starling-LM-7B-alpha. This merging strategy aims to combine the strengths of both base models.

Key Capabilities & Performance

This model demonstrates solid performance across a range of general language understanding and reasoning tasks, as evidenced by its evaluation on the Open LLM Leaderboard. Key benchmark results include:

• Average Score: 71.35
• ARC (25-shot): 67.75
• HellaSwag (10-shot): 86.23
• MMLU (5-shot): 65.24
• TruthfulQA (0-shot): 55.94
• Winogrande (5-shot): 81.45
• GSM8K (5-shot): 71.49

Usage

The model supports the ChatML format for instruction-following. With a context length of 4096 tokens, it is suitable for various conversational and text generation tasks where a balanced performance across general benchmarks is desired.