SmolLM - blazingly fast and remarkably powerful
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Loubna Ben Allal
loubnabnl
AI & ML interests
SmolLMs, ML for code, data
Recent Activity
new activity
6 days ago
HuggingFaceTB/finemath:Why did you use CC rather than FineWeb to create FineMath?
updated
a dataset
8 days ago
loubnabnl/mmlu-evals-smollm-360m
updated
a dataset
8 days ago
loubnabnl/code_data
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1675
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?
- 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?
Post
5365
🍷 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.
Technical report: HuggingFaceFW/blogpost-fineweb-v1
Dataset: HuggingFaceFW/fineweb-edu
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.
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.
Enjoy!
Technical report: HuggingFaceFW/blogpost-fineweb-v1
Dataset: HuggingFaceFW/fineweb-edu
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.
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.
Enjoy!
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loubnabnl/test
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loubnabnl/smollm-135M-instruct-v2
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loubnabnl/smollm-1.7B-instruct-v2
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loubnabnl/smollm-360M-instruct-add-basics-w-math
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loubnabnl/smollm-135M-instruct-add-basics-w-math
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loubnabnl/smollm-350M-instruct-add-basics-eq
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loubnabnl/smollm-350M-instruct-add-basics-only
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loubnabnl/SmolLM-360M-4bit
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loubnabnl/smollm-350M-instruct-test2-noOH
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loubnabnl/smollm-350M-instruct-test2-ep2
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loubnabnl/mmlu-evals-smollm-360m
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loubnabnl/code_data
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loubnabnl/english-web-100k
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loubnabnl/generations_dataset_sysprompt
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loubnabnl/gens-360M-temp7-v2
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loubnabnl/gens-360M-v2
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loubnabnl/gens-135M-v2
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loubnabnl/generations_dataset
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loubnabnl/example-generations
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loubnabnl/bisac_subset
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