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- Update README.md (c71b88f000bf7c92e553ad9e235a726b11f8d545)

README.md

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----
-license: apache-2.0
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+---
+license: odc-by
+task_categories:
+- text-generation
+language:
+- en
+pretty_name: Zyda
+size_categories:
+- n>1T
+---
+
+Zyda is a unified dataset, released under a permissive license, comprising most of the largest and highest quality existing open-source datasets available. 
+Upon these, we have performed extensive additional filtering, beyond what was originally applied, and thorough intra- and inter-dataset deduplication. 
+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
+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 
+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.
+
+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 
+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 
+necessary for training frontier models. Collating, filtering, and deduplicating the existing datasets needed to create a trillion token dataset is 
+nontrivial work and extremely important to raise the quality of the dataset and prevent significant amounts of inter-dataset duplicates. 
+This latter operation of deduplication between datasets is extremely important given the degree of duplicated documents we discovered in 
+the datasets that we collected in this work. 
+
+Here we are releasing a version of the dataset that was deduplicated using LSH minhash technique with 40% Jaccard similarity threshold.