|
--- |
|
license: other |
|
license_name: impact-license-medium-risk |
|
license_link: https://allenai.org/licenses/impact-mr |
|
viewer: false |
|
task_categories: |
|
- text-generation |
|
language: |
|
- en |
|
tags: |
|
- language-modeling |
|
- casual-lm |
|
- llm |
|
pretty_name: Dolma |
|
size_categories: |
|
- n>1T |
|
extra_gated_prompt: "Access to this dataset is automatically granted upon accepting the [**AI2 ImpACT License - Medium Risk Artifacts (“MR Agreement”)**](https://allenai.org/licenses/impact-mr) and completing all fields below." |
|
extra_gated_fields: |
|
Your full name: text |
|
Organization or entity you are affiliated with: text |
|
State or country you are located in: text |
|
Contact email: text |
|
Please describe your intended use of the medium risk artifact(s): text |
|
I AGREE to the terms and conditions of the MR Agreement above: checkbox |
|
I AGREE to AI2’s use of my information for legal notices and administrative matters: checkbox |
|
I CERTIFY that the information I have provided is true and accurate: checkbox |
|
--- |
|
|
|
# Dolma |
|
|
|
<img alt="Dolma's official logo. It's dolma written in yellow, round lowercase letters over a blue background." src="https://raw.githubusercontent.com/allenai/dolma/main/docs/assets/AI2_Blog_1400x685_2x.webp" width="100%"> |
|
|
|
Dolma is a dataset of 3 trillion tokens from a diverse mix of web content, academic publications, code, books, and encyclopedic materials. It is openly released under AI2’s ImpACT license as a medium risk artifact. |
|
|
|
|
|
More information: |
|
|
|
<https://github.com/allenai/dolma/blob/main/docs/assets/dolma-datasheet-v0.1.pdf> |
|
- Read Dolma **manuscript** and its **Data Sheet** [on ArXiv](https://github.com/allenai/dolma/blob/soldni/paper/docs/assets/dolma-v1_6-20240131.pdf); |
|
- Review Dolma's [**ImpACT license** for medium risk artifacts](https://allenai.org/licenses/impact-mr); |
|
- Explore the [**open source tools**](https://github.com/allenai/dolma) we created to curate Dolma. |
|
- Want to request removal of personal data? Use [this form](https://forms.gle/q4BNUUxUxKwKkfdT6) 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](https://github.com/allenai/dolma/tree/main/docs)! |
|
|
|
|
|
## Versions |
|
|
|
At the moment, there are five versions of Dolma available: |
|
|
|
| **Version** | **Default?** | **Release Date** | **Size** (gzip) | **Description** | |
|
|--|:--:|--|--|--| |
|
| `v1_6` | ✅ | 2024-01-31 | 5.4 TB | The latest version of Dolma, with 3 trillion tokens from a diverse mix of web content, academic publications, code, books, and encyclopedic materials. | |
|
| `v1_6-sample` | | 2024-01-31 | 16.4 GB | A smaller sample of Dolma, with roughly 10 billion tokens. Useful for data exploration. | |
|
| `v1_5` | | 2023-10-31 | 6.4 TB | The version of Dolma used to train [OLMo-1B](https://huggingface.co/allenai/OLMo-1B). Roughly 3 trillion tokens. | |
|
| `v1_5-sample` | | 2023-10-31 | 2.9 TB | A sample of roughly 1.9 trillion tokens used to train [OLMo-7B](https://huggingface.co/allenai/OLMo-7B) | |
|
| `v1` | | 2023-08-18 | 6.0 TB | The first version of Dolma. | |
|
|
|
(Size difference between `v1_6` and previous version is due to different set of metadata included in files: we removed redundant metadata in `v1_6`.) |
|
|
|
## Summary Statistics (v1.6) |
|
|
|
|
|
| **Source** | **Doc Type** | **UTF-8 bytes** (GB) | **Documents** (millions) | **Unicode words** (billions) | **Llama tokens** (billions) | |
|
|--|--|--|--|--|--| |
|
| Common Crawl | web pages | 9,022 | 3,370 | 1,775 | 2,281 | |
|
| The Stack | code| 1,043| 210 | 260| 411 | |
|
| C4 | web pages | 790 | 364 | 153| 198 | |
|
| Reddit| social media| 339 | 377| 72| 89 | |
|
| PeS2o | STEM papers| 268 | 38.8| 50| 70 | |
|
| Project Gutenberg | books | 20.4 | 0.056 | 4.0 | 6.0 | |
|
| Wikipedia, Wikibooks | encyclopedic | 16.2 | 6.2 | 3.7 | 4.3 | |
|
| **Total** | | **11,519** | **4,367** | **2,318** | **3,059** | |
|
|
|
|
|
|
|
## 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: |
|
|
|
```bash |
|
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: |
|
|
|
```python |
|
import os |
|
from datasets import load_dataset |
|
|
|
os.environ["DATA_DIR"] = "<path_to_your_data_directory>" |
|
dataset = load_dataset("allenai/dolma", split="train") |
|
``` |
|
|
|
## Bibtex |
|
|
|
If you use our dataset or tooling, please cite us at: |
|
|
|
```bibtex |
|
@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 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 Evan Pete Walsh and Hannaneh Hajishirzi and Noah A. Smith and Luke Zettlemoyer and |
|
Iz Beltagy and Dirk Groeneveld and Jesse Dodge and Kyle Lo |
|
}, |
|
year = {2024}, |
|
journal={arXiv preprint}, |
|
} |
|
``` |
|
|
