specific method · filed under data curation
Text-only pre-training corpus
Uses a trillions-of-tokens text-only corpus focused on STEM, coding, and general knowledge.
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How sources treat it
One count per evidence span, weakest treatment to strongest.
used 1
Documented in
Evidence
1 span quoted from the sources, strongest treatment first.
We train the models on a text-only dataset with trillions of tokens, with a focus on STEM, coding, and general knowledge.
useddata curationin gpt-oss-120b and gpt-oss-20bOpenAI
Filed alongside
Other methods under data curation :: data mixture & curriculum.
AutoMixerDeterministic pre-splitting of ultra-long documentsVulnerability-discovery data inclusionAgent-centric multimodal data mixtureAttribution, hedging, and refusal data subsetsBlind pairwise bucket-boundary calibrationData SchedulerDomain-specific multimodal datasetsDynamic sampling for mixed-task reinforcement learningFiltering, deduplication, and difficulty calibrationGaussian-based data mixture and curriculum constructionInterleaved dataInterleaved multimodal trainingKL-regularized data-mixture optimizationLong-context data upsamplingPass-rate-based RL task samplingPrior-constrained Dirichlet mixture explorationProtocolQA-aligned RL training datasetsSample MixerScaling-ladder-guided data and model planningSmooth weighted round-robin source schedulingThree-stage data mixture strategyThree-stage pre-training curriculumTwo-phase curriculum