Create README.md

README.md

@@ -0,0 +1,108 @@
+### 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      |
+
+The dataset consists of 2084 jsonl files, whose URLs are listed in the following file:
+```
+https://data.together.xyz/redpajama-data-1T/v1.0.0/urls.txt
+```
+
+To download the data, once can use 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).
+
+### Languages
+
+Primarily English, though the Wikipedia slice contains multiple languages.
+
+## Dataset Structure
+
+The dataset structure is as follows:
+
+```
+{
+    "text": ...,
+    "meta": {"url": "...", "timestamp": "...", "source": "...", "language": "...", ...}
+}
+```
+
+## 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.
+
+<!--
+### Annotations
+#### Annotation process
+[More Information Needed]
+#### Who are the annotators?
+[More Information Needed]
+### Personal and Sensitive Information
+[More Information Needed]
+## Considerations for Using the Data
+### Social Impact of Dataset
+[More Information Needed]
+### Discussion of Biases
+[More Information Needed]
+### Other Known Limitations
+[More Information Needed]
+## Additional Information
+### Dataset Curators
+[More Information Needed]
+### Licensing Information
+[More Information Needed]
+### Citation Information
+[More Information Needed]
+### Contributions
+[More Information Needed]
+-->