--- task_categories: - text-generation language: - en pretty_name: Red Pajama 1T --- ### Getting Started The dataset consists of 2084 jsonl files. You can download the dataset using HuggingFace: ``` ds = load_dataset("togethercomputer/RedPajama-Data-1T") ``` Or you can directly download the files using the following command: ``` wget -i https://data.together.xyz/redpajama-data-1T/v1.0.0/urls.txt ``` A smaller 1B-token sample of the dataset can be found [here](https://huggingface.co/datasets/togethercomputer/RedPajama-Data-1T-Sample). A full set of scripts to recreate the dataset from scratch can be found [here](https://github.com/togethercomputer/RedPajama-Data). ### Dataset Summary RedPajama is a clean-room, fully open-source implementation of the LLaMa dataset. | Dataset | Token Count | |---------------|-------------| | Commoncrawl | 878 Billion | | C4 | 175 Billion | | GitHub | 59 Billion | | Books | 26 Billion | | ArXiv | 28 Billion | | Wikipedia | 24 Billion | | StackExchange | 20 Billion | | Total | 1.2 Trillion | ### Languages Primarily English, though the Wikipedia slice contains multiple languages. ## Dataset Structure The dataset structure is as follows: ``` { "text": ..., "meta": {"url": "...", "timestamp": "...", "source": "...", "language": "...", ...}, "red_pajama_subset": "common_crawl" | "c4" | "github" | "books" | "arxiv" | "wikipedia" | "stackexchange" } ``` ## Dataset Creation This dataset was created to follow the LLaMa paper as closely as possible to try to reproduce its recipe. ### Source Data #### Commoncrawl We download five dumps from Commoncrawl, and run the dumps through the official `cc_net` pipeline. We then deduplicate on the paragraph level, and filter out low quality text using a linear classifier trained to classify paragraphs as Wikipedia references or random Commoncrawl samples. #### C4 C4 is downloaded from Huggingface. The only preprocessing step is to bring the data into our own format. #### GitHub The raw GitHub data is downloaded from Google BigQuery. We deduplicate on the file level and filter out low quality files and only keep projects that are distributed under the MIT, BSD, or Apache license. #### Wikipedia We use the Wikipedia dataset available on Huggingface, which is based on the Wikipedia dump from 2023-03-20 and contains text in 20 different languages. The dataset comes in preprocessed format, so that hyperlinks, comments and other formatting boilerplate has been removed. #### Gutenberg and Books3 The PG19 subset of the Gutenberg Project and Books3 datasets are downloaded from Huggingface. After downloading, we use simhash to remove near duplicates. #### ArXiv ArXiv data is downloaded from Amazon S3 in the `arxiv` requester pays bucket. We only keep latex source files and remove preambles, comments, macros and bibliographies. #### Stackexchange The Stack Exchange split of the dataset is download from the [Internet Archive](https://archive.org/download/stackexchange). Here we only keep the posts from the 28 largest sites, remove html tags, group the posts into question-answer pairs, and order answers by their score. ### License Please refer to the licenses of the data subsets you use. * [Common Crawl Foundation Terms of Use](https://commoncrawl.org/terms-of-use/full/) * [C4 license](https://huggingface.co/datasets/allenai/c4#license) * GitHub was limited to MIT, BSD, or Apache licenses only * Books: [the_pile_books3 license](https://huggingface.co/datasets/the_pile_books3#licensing-information) and [pg19 license](https://huggingface.co/datasets/pg19#licensing-information) * [ArXiv Terms of Use](https://info.arxiv.org/help/api/tou.html) * [Wikipedia License](https://huggingface.co/datasets/wikipedia#licensing-information) * [StackExchange license on the Internet Archive](https://archive.org/details/stackexchange)