Update README.md

README.md

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----
-license: mit
----
+---
+license: mit
+pretty_name: OpenWebText n-grams
+size_categories:
+- 100K<n<1M
+tags:
+- openwebtext
+- gpt2
+---
+
+This dataset contains the most common 1-6 contiguous token subsequences (n-grams) in an [open-source replication of the OpenWebText (OWT) dataset](https://huggingface.co/datasets/Skylion007/openwebtext). The OWT replication was compiled by Aaron Gokaslan and Vanya Cohen of Brown University.
+
+Below, we list the number of n-grams included. Alongside each, we show the minimum number of times each sequence occurs in the ~9B-token dataset (its frequency). We include all individual tokens (1-grams). Note that if an n-gram occurs >N times, then every contiguous subsequence must also occur >N times.
+
+| dataset           | total  | n=1   | n=2    | n=3    | n=4    | n=5    | n=6    |
+| ---               | -----  |------ | ------ | ------ | ------ | ------ | ------ |
+| owt_1-6grams_246k | 245831 | 50257 (freq >= 0) | 58302 (freq >= 10000)  | 44560 (freq >= 10000)  | 32831 (freq > 5000) | 13566 (freq > 5000) | 12495 (freq > 2000) |
+
+This dataset was used by the authors to show that gpt2-small sparse autoencoders memorize the most commonly presented n-grams more exactly.