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using distilabel (powers our new SFT dataset "},{"type":"resource","resource":{"type":"dataset","id":"HuggingFaceTB/smoltalk"},"url":"https://huggingface.co/datasets/HuggingFaceTB/smoltalk","raw":"https://huggingface.co/datasets/HuggingFaceTB/smoltalk"},{"type":"text","value":")","raw":")"},{"type":"new_line","raw":"\n"},{"type":"text","value":"- Post-training scripts with TRL & the alignment handbook","raw":"- Post-training scripts with TRL & the alignment handbook"},{"type":"new_line","raw":"\n"},{"type":"text","value":"- On-device tools with llama.cpp for summarization, rewriting & agents","raw":"- On-device tools with llama.cpp for summarization, rewriting & agents"},{"type":"new_line","raw":"\n"},{"type":"new_line","raw":"\n"},{"type":"text","value":"Apache 2.0 licensed. V2 pre-training data mix coming soon!","raw":"Apache 2.0 licensed. V2 pre-training data mix coming soon!"},{"type":"new_line","raw":"\n"},{"type":"new_line","raw":"\n"},{"type":"text","value":"Which other tools should we add next?","raw":"Which other tools should we add next?"}],"rawContent":"Making SmolLM2 reproducible: open-sourcing our training & evaluation toolkit 🛠️ https://github.com/huggingface/smollm/\n\n- Pre-training code with nanotron\n- Evaluation suite with lighteval\n- Synthetic data generation using distilabel (powers our new SFT dataset https://huggingface.co/datasets/HuggingFaceTB/smoltalk)\n- Post-training scripts with TRL & the alignment handbook\n- On-device tools with llama.cpp for summarization, rewriting & agents\n\nApache 2.0 licensed. 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We're releasing both FineWeb-Edu and the classifier, along with a larger, less heavily filtered version containing 5.4 trillion tokens. ","raw":"We used Llama 3 generations to train an educational quality classifier, filtering the 15 trillion tokens of FineWeb to select only those with high educational value (an approach also used in Llama 3 and Phi-3 training datasets). We're releasing both FineWeb-Edu and the classifier, along with a larger, less heavily filtered version containing 5.4 trillion tokens. "},{"type":"new_line","raw":"\n"},{"type":"new_line","raw":"\n"},{"type":"text","value":"You can find more details about the dataset and the experiments we ran in the FineWeb technical report, It's a 45-minute read but it contains all the secret sauce for building high quality web datasets.","raw":"You can find more details about the dataset and the experiments we ran in the FineWeb technical report, It's a 45-minute read but it contains all the secret sauce for building high quality web datasets."},{"type":"new_line","raw":"\n"},{"type":"new_line","raw":"\n"},{"type":"text","value":"Enjoy!","raw":"Enjoy!"}],"rawContent":"🍷 FineWeb technical report is out and so is 📚 FineWeb-Edu, a 1.3 trillion tokens dataset that outperforms all other open web datasets, with remarkable improvements on educational benchmarks such as MMLU, ARC, and OpenBookQA.\n\nTechnical report: https://hf.co/spaces/HuggingFaceFW/blogpost-fineweb-v1 \nDataset: https://hf.co/datasets/HuggingFaceFW/fineweb-edu \n\nWe used Llama 3 generations to train an educational quality classifier, filtering the 15 trillion tokens of FineWeb to select only those with high educational value (an approach also used in Llama 3 and Phi-3 training datasets). 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Loubna Ben Allal

loubnabnl

AI & ML interests

SmolLMs, ML for code, data

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liked a dataset 2 days ago
open-r1/codeforces-cots
upvoted an article 2 days ago
Open R1: Update #3
published an article 2 days ago
Open R1: Update #3
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3052
Making SmolLM2 reproducible: open-sourcing our training & evaluation toolkit 🛠️ https://github.com/huggingface/smollm/

- Pre-training code with nanotron
- Evaluation suite with lighteval
- Synthetic data generation using distilabel (powers our new SFT dataset HuggingFaceTB/smoltalk)
- Post-training scripts with TRL & the alignment handbook
- On-device tools with llama.cpp for summarization, rewriting & agents

Apache 2.0 licensed. V2 pre-training data mix coming soon!

Which other tools should we add next?

Articles 9

Article
197

Open R1: Update #3