Recent advancements in Large Language Models (LLMs) have been largely driven by enhancements in pre-training datasets. New data curation strategies are being explored, including leveraging synthetic data not only to create high-quality samples but also to develop classifiers that filter web content effectively.In this talk, we will discuss the methodologies behind the creation of the Cosmopedia and FineWeb-Edu datasets and how they led to the development of SmolLM models —a series of compact yet powerful LLMs.
Recent advancements in Large Language Models (LLMs) have been largely driven by enhancements in pre-training datasets. New data curation strategies are being explored, including leveraging synthetic data not only to...
Significance for Cancer Diagnosis Biomarkers (short for biological marker) are measurable biological indicators that provide crucial information about health status, disease processes, or treatment responses. Biomarkers can be molecules, genes,...
Medicine’s fundamental goal is to assist patients in managing and improving their health conditions. However, the language used within medical settings can sometimes inadvertently impact patients negatively, influencing their experiences...
Healthcare NLP employs advanced filtering techniques to refine entity recognition by excluding irrelevant entities based on specific criteria like whitelists or regular expressions. This approach is essential for ensuring precision...
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