metadata
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 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:
c4_realnews: The RealNews domain subset of the C4 dataset containing news articles.openwebtext: The OpenWebText dataset containing the contents of the links mentioned in Reddit posts with at least 3 upvotes.peS2o: The PeS2o dataset containing academic articles from Semantic Scholar.redpajama_books: The books subset of RedPajama V1.stackexchange: The EN StackExchange non-code subset of the BigScience ROOTs dataset.uspto: The EN USPTO patent applications contents' subset of the BigScience ROOTs dataset.wiki: The EN Wiki subset of the BigScience ROOTs dataset.
The following processing and filtering steps have been applied:
- Removed citation text and bibliography information for academic texts.
- 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.
- Removed samples which have a repeating <=4-gram proportion of 15%.
- Removed samples which have lower than 99% confidence of being EN using the lingua language detector.
- Performed an aggressive MinHash de-dupe using a shingle size of 8 and a low threshold of 0.5.