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OctoThinker/
MegaMath-Web-Pro-Max

Name: MegaMath-Web-Pro-Max
Creator: OctoThinker
License: https://spdx.org/licenses/ODC-By-1.0.html

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	OctoThinker: Mid-training Incentivizes Reinforcement Learning Scaling





	
	The Curation of MegaMath-Web-Pro-Max

Step 1: Uniformly and randomly sample millions of documents from the MegaMath-Web corpus, stratified by publication year; Step 2: Annotate them using Llama-3.1-70B-instruct with a scoring prompt from FineMath and prepare the seed data; Step 3: Training a fasttext carefully with proper preprocessing; Step 4: Filtering documents with a threshold (i.e., 0.4); Step 5:… See the full description on the dataset page: https://huggingface.co/datasets/OctoThinker/MegaMath-Web-Pro-Max.