The mini_reasoning_1k dataset is designed for enhancing efficient, concise reasoning in language models. Unlike longer chain-of-thought datasets that generate excessive tokens before converging on a solution, this dataset adopts a Short Chain of Thought (Short-CoT) approach, enabling models to perform accurate reasoning while minimizing token usage — crucial for improving inference speed and reducing computational cost.
🎯 Purpose and Scope… See the full description on the dataset page: https://huggingface.co/datasets/KingNish/mini_reasoning_1k.
