Dolma

Dolma is a dataset of 3 trillion tokens from a diverse mix of web content, academic publications, code, books, and encyclopedic materials.

More information:

• Read Dolma manuscript and its Data Sheet on ArXiv;
• Explore the open source tools we created to curate Dolma.
• Want to request removal of personal data? Use this form to notify us of documents containing PII about a specific user.

To learn more about the toolkit used to create Dolma, including how to replicate this dataset, head over our GitHub project page!

2024-04-17: Dolma v1.7 Release. We have released an updated version of Dolma that we used to train our latest OLMo 7B-v1.7 model.

2024-04-15: License Change. We have updated the license of Dolma to ODC-BY. Please see this blog post for more information.

Versions

At the moment, there are six versions of Dolma available:

Summary Statistics (v1.7)

(A subset of total data was used for training of OLMo 7B-v1.7. The token counts are based on the full dataset, whereas taking into account sampling proportion gives the final actual token counts used for training --- 1.715 trillion tokens.)

Summary Statistics (v1.6)

Download

The fastest way to download Dolma is to clone this repository and use the files in the url directory. We recommend using wget in parallel mode to download the files. For example:

DATA_DIR="<path_to_your_data_directory>"
PARALLEL_DOWNLOADS="<number_of_parallel_downloads>"
DOLMA_VERSION="<version_of_dolma_to_download>"

git clone https://huggingface.co/datasets/allenai/dolma
mkdir -p "${DATA_DIR}"


cat "dolma/urls/${DOLMA_VERSION}.txt" | xargs -n 1 -P "${PARALLEL_DOWNLOADS}" wget -q -P "$DATA_DIR"

Then, to load this data using HuggingFace's datasets library, you can use the following code:

import os
from datasets import load_dataset

os.environ["DATA_DIR"] = "<path_to_your_data_directory>"
dataset = load_dataset("allenai/dolma", split="train")

Licensing Information

We are releasing this dataset under the terms of ODC-BY. By using this dataset, you are also bound any license agreements and terms of use of the original data sources.

Bibtex

If you use our dataset or tooling, please cite us at:

@article{dolma,
  title = {{Dolma: an Open Corpus of Three Trillion Tokens for Language Model Pretraining Research}},
  author={
    Luca Soldaini and Rodney Kinney and Akshita Bhagia and Dustin Schwenk and David Atkinson and
    Russell Authur and Ben Bogin and Khyathi Chandu and Jennifer Dumas and Yanai Elazar and
    Valentin Hofmann and Ananya Harsh Jha and Sachin Kumar and Li Lucy and Xinxi Lyu and
    Nathan Lambert and Ian Magnusson and Jacob Morrison and Niklas Muennighoff and Aakanksha Naik and
    Crystal Nam and Matthew E. Peters and Abhilasha Ravichander and Kyle Richardson and Zejiang Shen and
    Emma Strubell and Nishant Subramani and Oyvind Tafjord and Pete Walsh and Luke Zettlemoyer and
    Noah A. Smith and Hannaneh Hajishirzi and Iz Beltagy and Dirk Groeneveld and Jesse Dodge and Kyle Lo
  },
  year = {2024},
  journal={arXiv preprint},
}