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Exploring smol models and high quality web and synthetic datasets, generated by LLMs (TB is for Textbook, as inspired by the "Textbooks are all your need" paper)

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mfarre  published a Space 21 minutes ago
HuggingFaceTB/SmolVLM2-XSPFGenerator
mfarre  published a Space 21 minutes ago
HuggingFaceTB/SmolVLM2-iPhone-waitlist
mfarre  published a Space 21 minutes ago
HuggingFaceTB/SmolVLM2-HighlightGenerator
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HuggingFaceTB

This is the home for smol models (SmolLM & SmolVLM) and high quality pre-training datasets. We released:

  • FineWeb-Edu: a filtered version of FineWeb dataset for educational content, paper available here.
  • Cosmopedia: the largest open synthetic dataset, with 25B tokens and 30M samples. It contains synthetic textbooks, blog posts, and stories, posts generated by Mixtral. Blog post available here.
  • Smollm-Corpus: the pre-training corpus of SmolLM: Cosmopedia v0.2, FineWeb-Edu dedup and Python-Edu. Blog post available here.
  • SmolLM2 models: a series of strong small models in three sizes: 135M, 360M and 1.7B
  • SmolVLM: a 2 billion Vision Language Model (VLM) built for on-device inference. It uses SmolLM2-1.7B as a language backbone. Blog post available here.
  • FineMath: the best public math pretraining dataset with 50B tokens of mathematical and problem solving data.

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