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@@ -135,4 +135,6 @@ Recently, IBM has introduced GneissWeb; a large dataset yielding around 10 trill
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5. [Notebook](https://github.com/IBM/data-prep-kit/blob/dev/examples/notebooks/GneissWeb/GneissWeb.ipynb) to recreate GneissWeb using the methods described above :
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6. [Notebook](https://github.com/ian-cho/data-prep-kit/tree/dev/transforms/universal/bloom) to recreate GneissWeb using a bloom filter built on the document ids of GneissWeb
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5. [Notebook](https://github.com/IBM/data-prep-kit/blob/dev/examples/notebooks/GneissWeb/GneissWeb.ipynb) to recreate GneissWeb using the methods described above :
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6. [Notebook](https://github.com/ian-cho/data-prep-kit/tree/dev/transforms/universal/bloom) to recreate GneissWeb using a bloom filter built on the document ids of GneissWeb
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7. [Technical Report](https://huggingface.co/datasets/ibm-granite/GneissWeb/blob/main/GneissWebPaper_Feb21_2025.pdf) detailing the creation of GneissWeb
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