Mid-training and Multi-Dataset Adaptation
gabriberton · x · 2026-07-13
This post discusses a specific data processing strategy: standalone datasets like Wikipedia and GitHub are too small to train a model from scratch. Therefore, the workflow involves pre-training on noisier data, fine-tuning a separate LLM for each specific dataset, and subsequently running post-training.
This overall workflow is referred to here as mid-training.
Related event: LLM Data Curation Insights: Data Rebound and Mid-training(6 posts)→
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