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README.md

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 # HuggingFaceTB
-This is the home of synthetic datasets for pre-training, such as [Cosmopedia](https://huggingface.co/datasets/HuggingFaceTB/cosmopedia). We're trying to scale synthetic data generation by curating
+This is the home of synthetic datasets for pre-training, such as [Cosmopedia](https://huggingface.co/datasets/HuggingFaceTB/cosmopedia) v1 and v2. We're trying to scale synthetic data generation by curating
 diverse prompts that cover a wide range of topics and efficiently scaling the generations on GPUs with tools like [llm-swarm](https://github.com/huggingface/llm-swarm).
 
-We recently released:
+We released:
 
 - [Cosmopedia](https://huggingface.co/datasets/HuggingFaceTB/cosmopedia): the largest open synthetic dataset, with 25B tokens and more than 30M samples. It contains synthetic textbooks, blog posts, stories, posts, and WikiHow articles generated by Mixtral-8x7B-Instruct-v0.1.
 - [Cosmo-1B](https://huggingface.co/HuggingFaceTB/cosmo-1b) a 1B model trained on Cosmopedia.
+- [FineWeb-Edu](https://huggingface.co/datasets/HuggingFaceFW/fineweb-edu): a filtered version of FineWeb dataset for educational content
+- [SmolLM models](https://huggingface.co/collections/HuggingFaceTB/smollm-6695016cad7167254ce15966): a series of strong small models in three sizes: 135M, 360M and 1.7B
+- [Smollm-Corpus](https://huggingface.co/datasets/HuggingFaceTB/smollm-corpus): the pre-training corpus of SmolLM models including **Cosmopedia v0.2**, **FineWeb-Edu** and **Python-Edu**.
 
-For more details check our blogpost: https://huggingface.co/blog/cosmopedia
+For more details check our blog posts: https://huggingface.co/blog/cosmopedia and https://huggingface.co/blog/smollm