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# SkyPile-150B
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## Dataset Summary
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SkyPile-150B is
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The public part of SkyPile-150B contains approximately 166M individual web pages, with an average of over 1k Chinese characters, a total of approximately 150B tokens, and 592G plain text data.
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## Language
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SkyPile-150B is Chinese data.
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## Data Field
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text:
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## Sensitive
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## Social Impact of Dataset
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# SkyPile-150B
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## Dataset Summary
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SkyPile-150B is a comprehensive, large-scale Chinese dataset specifically designed for the pre-training of large language models. It is derived from a broad array of publicly accessible Chinese Internet web pages. Rigorous filtering, extensive deduplication, and thorough sensitive data filtering have been employed to ensure its quality. Furthermore, we have utilized advanced tools such as fastText and BERT to filter out low-quality data.
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The publicly accessible portion of the SkyPile-150B dataset encompasses approximately 166 million unique web pages, each containing an average of over 1,000 Chinese characters. In total, the dataset includes approximately 150 billion tokens and 592 gigabytes of plain text data.
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## Language
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The SkyPile-150B dataset is exclusively composed of Chinese data.
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## Data Field Explanation
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- text: the processed and cleaned text extracted from each page.
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## Sensitive Information and Bias
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Despite our best efforts, SkyPile-150B, given its construction from publicly available web pages, might contain sensitive information such as email addresses, phone numbers, or IP addresses. We have endeavored to minimize this through deduplication and low-quality filtering, but users of SkyPile-150B should remain vigilant.
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The Internet is rife with potentially toxic or biased data. We have attempted to mitigate this with specific URL filtering methods, but we encourage users to remain conscious of this potential issue.
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## Social Impact of the Dataset
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The open-source release of the SkyPile-150B dataset represents our commitment to enhancing access to high-quality web data, which has traditionally been a closely guarded resource among model developers. We believe that this release will foster greater accessibility and the proliferation of high-performance large language models, thereby contributing significantly to the advancement of the field.
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