Description: This fined-tuned LoRA layer is optimized for the specific task of generating structured data models in JSON format from a dump of tabular data files. It only requires headers from the tabular files, allowing usage in environments where the underlying data may require separate authorization. It is trained and evaluated against a diverse range of research data models, with this initial release leaning towards biomedical research data models (as the nature of the available real models and project tended towards this domain). This means it is likely better at handling typical biomedical datasets with research studies, patients, samples, genomics, imaging, etc. The creation of this model leveraged high quality synthetic data, generated from a custom algorithm which takes real, expert-curated, production data models in use today as input. The synthetic data generation algorithm addresses the challenge of providing a robust training foundation of high-quality data for AI-driven data model generation. Intended Use: This will act as an interim step in an overall AI-assisted data harmonization tool that is still under development. We are releasing this portion of the work…
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Генерация текста
Задача: Генерация текста
Автор: uc-ctds
Теги: en
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Описание основано на материалах HuggingFace. Перевод выполнен автоматически.
