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--- |
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dataset_info: |
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features: |
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- name: blob_id |
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dtype: string |
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- name: repo_name |
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dtype: string |
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- name: path |
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dtype: string |
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- name: length_bytes |
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dtype: int64 |
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- name: score |
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dtype: float64 |
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- name: int_score |
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dtype: int64 |
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- name: text |
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dtype: string |
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- name: download_success |
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dtype: bool |
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splits: |
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- name: train |
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num_bytes: 13499266964 |
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num_examples: 7678448 |
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download_size: 6086016638 |
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dataset_size: 13499266964 |
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configs: |
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- config_name: default |
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data_files: |
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- split: train |
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path: data/train-* |
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--- |
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# About This Dataset |
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The HuggingFaceTB team has released an impressive series of models called smollm (V1/V2) (paper： https://arxiv.org/abs/2502.02737). |
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According to their documentation, they used Stack-Edu as the code field corpus for pretraining and published https://huggingface.co/datasets/HuggingFaceTB/smollm-corpus. |
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However for some reason, only a Python-Edu subset is accessible and there's no content/text field in it. |
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The full dataset is stored on AWS S3; downloading it requires an AWS EC2 instance, or you will be blocked by AWS's rate limits under which you will never download it. |
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Fortunately, the py-edu subset is relatively small (~7 million files) for me to afford; downloading the entire set takes approximately one hour. |
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I am publishing the complete py-edu dataset here for anyone who needs it. |
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If this release inadvertently causes any issues for the HuggingFaceTB team, please reach out to me and I will remove it immediately. |
