datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
reasoning_world_modelMMMU-Reasoning-Distill-Validation中文版本
Description
MMMU-Reasoning-Distill-Validation is a Multi-Modal reasoning dataset that contains 839 image descriptions and natural language inference data samples. This dataset is built upon the validation set of MMMU. The construction process begins with using Qwen2.5-VL-72B-Instruct for image understanding and generating detailed image descriptions, followed by generating reasoning conversations using the DeepSeek-R1 model. Its main features are as follows:
Use the… See the full description on the dataset page: https://huggingface.co/datasets/modelscope/MMMU-Reasoning-Distill-Validation.ida-reasoning-model
IDA Reasoning Model
This model was trained using Imitation, Distillation, and Amplification (IDA) on multiple reasoning datasets.
Training Details
Teacher Model: deepseek-ai/DeepSeek-R1-Distill-Qwen-7B
Student Model: Qwen/Qwen3-1.7B
Datasets: 4 reasoning datasets
Total Samples: 600
Training Method: IDA (Iterative Distillation and Amplification)
Datasets Used
gsm8k
HuggingFaceH4/MATH-500
MuskumPillerum/General-Knowledge
SAGI-1/reasoningData_200k… See the full description on the dataset page: https://huggingface.co/datasets/ziadrone/ida-reasoning-model.ida-reasoning-model1humanoid-world-model-reasoning
Humanoid World Model Reasoning
Dataset for training internal world models and reasoning loops in humanoid AI.
quantitative_modeling_reasoning_v2advanced_mathematical_modelling_reasoning_v1