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README.md
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---
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license:
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---
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license: odc-by
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task_categories:
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- text-generation
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language:
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- en
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pretty_name: Zyda
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size_categories:
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- n>1T
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---
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Zyda is a unified dataset, released under a permissive license, comprising most of the largest and highest quality existing open-source datasets available.
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Upon these, we have performed extensive additional filtering, beyond what was originally applied, and thorough intra- and inter-dataset deduplication.
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Our aim with this work is to create a growing and extendable meta-dataset which can be easily used by practitioners to train trillion-token scale language models
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while also consolidating and unifying the efforts made by disparate open-source groups who have released their datasets. Ultimately, we hope that our work can
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provide an 'off-the-shelf' accessible trillion-scale high quality pretraining dataset which can be used by groups interested in pretraining their own LLM models.
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While not performing new filtering from common-crawl, we believe that our work is an important and valuable step towards the creation of large scale
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high quality open datasets given that there exist a number of high quality existing datasets but few to none of them individually reach the scale
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necessary for training frontier models. Collating, filtering, and deduplicating the existing datasets needed to create a trillion token dataset is
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nontrivial work and extremely important to raise the quality of the dataset and prevent significant amounts of inter-dataset duplicates.
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This latter operation of deduplication between datasets is extremely important given the degree of duplicated documents we discovered in
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the datasets that we collected in this work.
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Here we are releasing a version of the dataset that was deduplicated using LSH minhash technique with 40% Jaccard similarity threshold.
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