We trained a mini-O1 model and conducted validation and evaluation on the inference dataset to test its performance in real-world applications. The model has undergone multiple rounds of training and optimization, enabling it to efficiently process input data and generate reasonable predictions in inference tasks. Through experiments on the inference dataset, we assessed the model's accuracy, robustness, and inference speed across different scenarios, providing data support and theoretical foundation for further improvements and applications of the model.

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