| --- |
| configs: |
| - config_name: bytelevel |
| default: true |
| data_files: |
| - split: train |
| path: bytelevel2/*.parquet |
| - config_name: bytelevel-llm-data |
| data_files: |
| - split: fw57M |
| path: bytelevel-llm-data/fw57M/fw57M-* |
| - split: ngram |
| path: bytelevel-llm-data/ngram/ngram-* |
| - config_name: bytelevel-subset |
| data_files: |
| - split: train |
| path: bytelevel-subset/train-* |
| - config_name: bytelevel-subset_1 |
| data_files: |
| - split: train |
| path: bytelevel-subset_1/train-* |
| - config_name: bytelevel-subset_2 |
| data_files: |
| - split: train |
| path: bytelevel-subset_2/train-* |
| - config_name: BPE_64000 |
| data_files: |
| - split: train |
| path: BPE_64000/*.parquet |
| - config_name: ByteSpanSurprisalCombinedFrequency_64000 |
| data_files: |
| - split: train |
| path: ByteSpanSurprisalCombinedFrequency_64000/*.parquet |
| - config_name: ByteSpanSurprisalMonotonicFrequency_64000 |
| data_files: |
| - split: train |
| path: ByteSpanSurprisalMonotonicFrequency_64000/*.parquet |
| - config_name: ByteSpanSurprisalMonotonicSeeding_64000 |
| data_files: |
| - split: train |
| path: ByteSpanSurprisalMonotonicSeeding_64000/*.parquet |
| - config_name: ByteSpanSurprisalCombinedSeeding_64000 |
| data_files: |
| - split: train |
| path: ByteSpanSurprisalCombinedSeeding_64000/*.parquet |
| - config_name: ByteSpanSurprisalGlobalIncrement_64000 |
| data_files: |
| - split: train |
| path: ByteSpanSurprisalGlobalIncrement_64000/*.parquet |
| - config_name: BPEWP_64000 |
| data_files: |
| - split: train |
| path: BPEWP_64000/*.parquet |
| language: |
| - en |
| tags: |
| - language modeling |
| pretty_name: FineWebEDU 20B |
| size_categories: |
| - 10B<n<100B |
| --- |
| |
| # FineWebEDU 20B |
|
|
| A copy of [FineWebEDU-20B](https://huggingface.co/datasets/HuggingFaceFW/fineweb-edu) 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` |
|
|
|
|
