---
dataset_info:
- config_name: all
  features:
  - name: content
    dtype: string
  splits:
  - name: train
    num_bytes: 360187653412.6177
    num_examples: 56194997
  download_size: 199030076349
  dataset_size: 360187653412.6177
- config_name: c4_realnews
  features:
  - name: content
    dtype: string
  splits:
  - name: train
    num_bytes: 31597106256.723488
    num_examples: 11427438
  download_size: 19889880484
  dataset_size: 31597106256.723488
- config_name: openwebtext
  features:
  - name: content
    dtype: string
  splits:
  - name: train
    num_bytes: 30974178275.039234
    num_examples: 6474479
  download_size: 19069709415
  dataset_size: 30974178275.039234
- config_name: peS2o
  features:
  - name: content
    dtype: string
  splits:
  - name: train
    num_bytes: 221900508006.5479
    num_examples: 32612199
  download_size: 116217303065
  dataset_size: 221900508006.5479
- config_name: redpajama_books
  features:
  - name: content
    dtype: string
  splits:
  - name: train
    num_bytes: 49246538575.26426
    num_examples: 107443
  download_size: 29612204926
  dataset_size: 49246538575.26426
- config_name: stackexchange
  features:
  - name: content
    dtype: string
  splits:
  - name: train
    num_bytes: 2034535930.2150385
    num_examples: 716532
  download_size: 1222605537
  dataset_size: 2034535930.2150385
- config_name: uspto
  features:
  - name: content
    dtype: string
  splits:
  - name: train
    num_bytes: 14755999149.910166
    num_examples: 3247716
  download_size: 7058272149
  dataset_size: 14755999149.910166
- config_name: wiki
  features:
  - name: content
    dtype: string
  splits:
  - name: train
    num_bytes: 7528525537.163156
    num_examples: 1609190
  download_size: 4593971902
  dataset_size: 7528525537.163156
configs:
- config_name: all
  data_files:
  - split: train
    path: all/train-*
- config_name: c4_realnews
  data_files:
  - split: train
    path: c4_realnews/train-*
- config_name: openwebtext
  data_files:
  - split: train
    path: openwebtext/train-*
- config_name: peS2o
  data_files:
  - split: train
    path: peS2o/train-*
- config_name: redpajama_books
  data_files:
  - split: train
    path: redpajama_books/train-*
- config_name: stackexchange
  data_files:
  - split: train
    path: stackexchange/train-*
- config_name: uspto
  data_files:
  - split: train
    path: uspto/train-*
- config_name: wiki
  data_files:
  - split: train
    path: wiki/train-*
task_categories:
- text-generation
language:
- en
size_categories:
- 10M<n<100M
---

A small, aggressively cleaned and de-duped pre-training corpus for academic settings. It aims to recreate something akin to [The Pile](https://huggingface.co/datasets/EleutherAI/pile) but prioritizes quality for the constrained token budget academic researchers live with.

It has seven config subsets and an eighth `all` subset that combines them for a total of ~91B tokens (GPT2 Tokenizer estimate). These splits are as follows:

1. `c4_realnews`: The RealNews domain subset of the C4 dataset containing news articles.
2. `openwebtext`: The OpenWebText dataset containing the contents of the links mentioned in Reddit posts with at least 3 upvotes.
3. `peS2o`: The PeS2o dataset containing academic articles from Semantic Scholar.
4. `redpajama_books`: The books subset of RedPajama V1.
5. `stackexchange`: The EN StackExchange non-code subset of the BigScience ROOTs dataset.
6. `uspto`: The EN USPTO patent applications contents' subset of the BigScience ROOTs dataset.
7. `wiki`: The EN Wiki subset of the BigScience ROOTs dataset.

The following processing and filtering steps have been applied:

1. Removed citation text and bibliography information for academic texts.
2. Ran a perplexity filter using a KenLM model trained on the EN OSCAR corpus and removed documents with a perplexity of more than 325 and less than 7.
3. Removed samples which have a repeating <=4-gram proportion of 15%.
4. Removed samples which have lower than 99% confidence of being EN using the lingua language detector.
5. Performed an aggressive MinHash de-dupe using a shingle size of 8 and a low threshold of 0.5.