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structured

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relflow

RelFlow turns nested, ragged data into neural representations. It lets users define typed schemas: numbers, categories, sets, dates, entities, text, etc., then trains models for prediction and embeddings. The library supports MLM-based pretraining workflows, mutations, and serving. It is built for data that does not fit cleanly into flat tables.

  • Updated Aug 26, 2026
  • Python

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