README.md

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title: README
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# HuggingFaceTB
This is the home for smol models (SmolLM) and high quality pre-training datasets.


We released:

- [FineWeb-Edu](https://huggingface.co/datasets/HuggingFaceFW/fineweb-edu): a filtered version of FineWeb dataset for educational content, paper available [here](https://huggingface.co/papers/2406.17557).
- [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. Blog post available [here](https://huggingface.co/blog/cosmopedia).
- [Smollm-Corpus](https://huggingface.co/datasets/HuggingFaceTB/smollm-corpus): the pre-training corpus of SmolLM models including **Cosmopedia v0.2**, **FineWeb-Edu dedup** and **Python-Edu**. Blog post available [here](https://huggingface.co/blog/smollm).
- [SmolLM models](https://huggingface.co/collections/HuggingFaceTB/smollm-6695016cad7167254ce15966) and [SmolLM2 models](https://huggingface.co/collections/HuggingFaceTB/smollm2-checkpoints-6723884218bcda64b34d7db9): a series of strong small models in three sizes: 135M, 360M and 1.7B


**News 🗞️**
- SmolLM2: you can find our most capable model SmolLM2-1.7B here: https://huggingface.co/HuggingFaceTB/SmolLM2-1.7B-Instruct
- We released our SFT mix SmolTalk, a diverse dataset of 1M synthetic instruction and answer pairs to improve instruction following and reasoning: https://huggingface.co/datasets/HuggingFaceTB/smoltalk


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<img src="https://cdn-uploads.huggingface.co/production/uploads/61c141342aac764ce1654e43/uS1E7sToFiE5Bv5ENa_ot.png" width="800"/>
<p><em>Comparison of models finetuned on SmolTalk and Orca AgentInstruct 1M. For more details, refer to the <a href="https://huggingface.co/datasets/HuggingFaceTB/smoltalk" target="_blank">dataset card</a>.</em></p>
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