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dict
[ 2.6633928537368776, 2.889687418937683, 3.1006414890289307, 3.3050988912582397, 3.5178554534912108 ]
{ "mean": 3.1054143247001487, "std": 0.41193265989987327, "min": 0.517546534538269, "max": 6.902653694152832 }
[ 2.660422444343567, 2.888396978378296, 3.0999048948287964, 3.304680109024048, 3.5141592979431153 ]
{ "mean": 3.104386346171307, "std": 0.41453052906744825, "min": 0.727095901966095, "max": 6.743678092956543 }
[ 2.660422444343567, 2.888396978378296, 3.0999048948287964, 3.304680109024048, 3.5141592979431153 ]
{ "mean": 3.104386346171307, "std": 0.41453052906744825, "min": 0.727095901966095, "max": 6.743678092956543 }
[ 2.668377423286438, 2.893209397792816, 3.1050426959991455, 3.3114383220672607, 3.5287172317504885 ]
{ "mean": 3.1132298165873857, "std": 0.41943169777515676, "min": 0.46505701541900635, "max": 7.135637283325195 }
[ 2.668377423286438, 2.893209397792816, 3.1050426959991455, 3.3114383220672607, 3.5287172317504885 ]
{ "mean": 3.1132298165873857, "std": 0.41943169777515676, "min": 0.46505701541900635, "max": 7.135637283325195 }
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FineWeb Dataset - GPT-2 Tokenized

This dataset contains preprocessed and tokenized FineWeb data using the GPT-2 tokenizer. It consists of multiple training folders containing the processed data.

Dataset structure:

  • fineweb_train_000001 to fineweb_train_000005: Training folders
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