--- 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.