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id
string
input_ids
sequence
num_tokens
int64
<urn:uuid:0d8a309d-25c5-405d-a08a-c11239f0d717>
[ 222, 53, 73, 70, 222, 42, 79, 69, 70, 81, 70, 79, 69, 70, 79, 85, 222, 43, 66, 79, 70, 200, 39, 80, 83, 222, 66, 77, 77, 222, 85, 73, 70, 222, 77, 80, 87, 70, 13, 222, 83, 80, 78, 66, 79, 68, 70, 222, 66, 79, 69, 2...
3,728
<urn:uuid:7400301c-e625-46d5-be90-1020cf8d52f8>
[ 222, 53, 80, 83, 79, 66, 69, 80, 70, 84, 222, 66, 83, 70, 222, 85, 73, 70, 222, 78, 80, 84, 85, 222, 74, 79, 85, 70, 79, 84, 70, 222, 84, 85, 80, 83, 78, 84, 222, 80, 79, 222, 85, 73, 70, 222, 81, 77, 66, 79, 70, 8...
2,570
<urn:uuid:f166f15d-9976-40ed-8a49-8bed360001ff>
[ 222, 42, 84, 222, 85, 73, 74, 84, 222, 67, 80, 79, 70, 222, 66, 222, 47, 70, 66, 79, 69, 70, 83, 85, 73, 66, 77, 222, 71, 77, 86, 85, 70, 32, 200, 36, 66, 87, 70, 222, 35, 70, 66, 83, 222, 71, 70, 78, 86, 83, 222, ...
10,329
<urn:uuid:ca387b2a-7df2-4bb1-8e2d-9e82dcdc8b5a>
[ 222, 37, 74, 68, 85, 74, 80, 79, 66, 83, 90, 222, 66, 79, 69, 222, 85, 83, 66, 79, 84, 77, 66, 85, 80, 83, 222, 71, 80, 83, 222, 73, 66, 79, 69, 73, 70, 77, 69, 200, 47, 70, 88, 222, 27, 222, 84, 70, 79, 84, 66, 72...
23,081
<urn:uuid:6aba2b8d-0f86-4d64-b8af-a03c21e98c63>
[ 222, 42, 79, 222, 84, 80, 78, 70, 222, 81, 70, 80, 81, 77, 70, 13, 222, 78, 66, 68, 86, 77, 66, 83, 222, 69, 70, 72, 70, 79, 70, 83, 66, 85, 74, 80, 79, 222, 66, 69, 87, 66, 79, 68, 70, 84, 222, 84, 80, 222, 84, 77...
1,766
<urn:uuid:81426048-4862-4bb7-9a74-922f76b4cc47>
[ 222, 53, 73, 70, 83, 70, 222, 66, 83, 70, 222, 78, 66, 79, 90, 222, 88, 66, 90, 84, 222, 85, 80, 222, 70, 71, 71, 70, 68, 85, 74, 87, 70, 77, 90, 222, 85, 70, 66, 68, 73, 222, 66, 222, 69, 80, 72, 15, 200, 47, 80, ...
3,374
<urn:uuid:e36683d3-ded6-4e38-af4d-7bc73d1ec7e3>
[ 222, 39, 70, 88, 70, 83, 222, 83, 66, 83, 70, 222, 84, 70, 66, 222, 85, 86, 83, 85, 77, 70, 84, 222, 88, 74, 77, 77, 222, 69, 74, 70, 222, 80, 79, 222, 85, 73, 70, 222, 84, 88, 80, 83, 69, 71, 74, 84, 73, 222, 74, ...
3,510
<urn:uuid:4dcad241-2b6b-4970-9112-c67a47a29a2c>
[ 222, 34, 222, 67, 86, 77, 77, 80, 68, 76, 222, 68, 66, 83, 85, 222, 80, 83, 222, 80, 89, 222, 68, 66, 83, 85, 222, 74, 84, 222, 66, 222, 85, 88, 80, 14, 88, 73, 70, 70, 77, 70, 69, 222, 80, 83, 222, 71, 80, 86, 83, ...
1,953
<urn:uuid:6c5322ef-413f-4a69-b643-e15509f4014a>
[222,93,35,74,83,85,73,222,79,66,78,70,93,93,47,80,83,78,66,79,222,49,70,83,68,70,87,70,77,222,51,80(...TRUNCATED)
20,497
<urn:uuid:983e5733-551c-4c84-be58-6e25791db2ab>
[222,53,73,70,222,79,66,78,70,84,222,68,73,74,84,70,77,70,69,222,80,79,85,80,222,68,74,85,90,222,85,(...TRUNCATED)
928
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FineWebEDU 20B

A copy of FineWebEDU-20B used for out tokenizer experiments. The subsets are as follows:

  • bytelevel: the full dataset tokenized using our bytelevel tokenizer
  • bytelevel-subset_1: a 100k-row subset of the bytelevel subset, used to train bytelevel models.
  • bytelevel-subset_2: a 100k-row subset of the bytelevel subset, used to extract llm predictions.
  • bytelevel-llm-data: a copy of bytelevel-subset_2 with lm predictions, used to train bytespan tokenizers
  • bytelevel-subset_3: a 100k-row subset of the bytelevel subset, used to evaluate trained tokenizers

The remaining subsets are all versions of the dataset tokenized with our trained tokenizers:

  • BPE_64000
  • BPEWP_64000
  • ByteSpanSurprisalMonotonicFrequency_64000
  • ByteSpanSurprisalMonotonicSeeding_64000
  • ByteSpanSurprisalCombinedFrequency_64000
  • ByteSpanSurprisalCombinedSeeding_64000
  • ByteSpanSurprisalGlobalIncrement_64000
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