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@@ -14,20 +14,27 @@ If you are training base language models and want the cleanest sources available
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  ### Dataset Description
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- All data added to OCD has been cleaned to ensure the highest possible quality. Part of this process includes manually inspecting (and sometimes manually fixing) thousands of documents.
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- Whenever defects are found (from e.g. conversion errors), they will be fixed for the next major version.
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  ### Dataset Sources
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- OCD currently consists of 2 major subsets:
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- - Web data originating from [C4](https://huggingface.co/datasets/c4). This subset was heavily filtered to remove a lot of spam and templates. It consists of approximately 18M documents, which is roughly 5% of the original 365M documents.
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- - Peer reviewed research originating from [PLOS](https://plos.org/text-and-data-mining/). Documents were normalized to markdown from the original JATS XML, and were processed to remove captions and references to missing figures. A large number of these documents were manually inspected to remove irrelevant files (e.g. PLOS announcements, letters to the editor, and short comments).
 
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- This dataset is actively in development, and will soon be extended to include various domains, including (appropriately licensed) books, research from other sources, code, and more.
 
 
 
 
 
 
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  ## Uses
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- The primary intended use of this dataset is for training base language models. Given this, emphasis is put on gathering high quality data from a variety of sources.
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  ### Dataset Description
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+ It is without question that the quality of a language model rests on the quality of its training data. OCD is a meticulously curated and cleaned corpus of text documents, ensuring the highest quality text from a variety of sources. Part of this process includes manually inspecting (and sometimes manually fixing) thousands of documents.
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+ Whenever problem documents are found (from e.g. conversion errors, or spam that got through), they are fixed for the next release.
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  ### Dataset Sources
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+ OCD currently consists of 3 subsets:
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+ - Web data originating from [C4](https://huggingface.co/datasets/c4). This subset was heavily filtered to remove a lot of spam, templates, and other low quality data. It consists of approximately 18M documents, which is roughly 5% of the original 365M documents.
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+ - Peer reviewed research originating from [PLOS](https://plos.org/text-and-data-mining/). Documents were normalized to markdown from the original JATS XML, and were processed to remove captions and references to missing figures. A large number of these documents were manually inspected to remove irrelevant files (e.g. journal announcements, letters to the editor, and short comments).
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+ - Non-fiction books from [CCOpenBooks](https://huggingface.co/datasets/Daniel-P-Gonzalez/CCOpenBooks). This will be expanded soon, as the original collection was quite small. However, it contains only high quality text books, all of which have non-restrictive cc-by compatible licenses.
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+ This dataset is actively in development, and will continue to be extended to include books, research, and other documents from various domains, code, documentation, and more.
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+ ## License
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+ OCD is released under the cc-by-4.0 license. Note that this is directly compatible with [PLOS](https://plos.org/terms-of-use/) and CCOpenBooks ([cc-by-4.0](https://huggingface.co/datasets/Daniel-P-Gonzalez/CCOpenBooks)).
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+ Documents originating from C4 were released under the ODC-BY license as noted [here](https://huggingface.co/datasets/c4#licensing-information). As this subset was derived from an enormous Common Crawl corpus, there is a possibility that it contains documents not compatible with this license. However, the heavy filtering applied as part of the OCD project greatly reduces this possibility. Additionally, any opt-out requests from content authors will be respected.
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  ## Uses
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+ The primary intended use of this dataset is for training base language models.
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