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--- |
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license: other |
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license_name: impact-license-medium-risk |
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license_link: https://allenai.org/licenses/impact-mr |
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viewer: true |
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task_categories: |
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- text-generation |
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language: |
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- en |
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tags: |
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- language-modeling |
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- casual-lm |
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- llm |
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pretty_name: Dolma |
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size_categories: |
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- n>1T |
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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." |
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extra_gated_fields: |
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Your full name: text |
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Organization or entity you are affiliated with: text |
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State or country you are located in: text |
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Contact email: text |
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Please describe your intended use of the medium risk artifact(s): text |
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I AGREE to the terms and conditions of the MR Agreement above: checkbox |
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I AGREE to AI2’s use of my information for legal notices and administrative matters: checkbox |
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I CERTIFY that the information I have provided is true and accurate: checkbox |
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--- |
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# Dolma |
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<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%"> |
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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. |
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More information: |
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<https://github.com/allenai/dolma/blob/main/docs/assets/dolma-datasheet-v0.1.pdf> |
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- Read Dolma **manuscript** and its **Data Sheet** [on ArXiv](https://github.com/allenai/dolma/blob/soldni/paper/docs/assets/dolma-v1_6-20240131.pdf); |
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- Review Dolma's [**ImpACT license** for medium risk artifacts](https://allenai.org/licenses/impact-mr); |
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- Explore the [**open source tools**](https://github.com/allenai/dolma) we created to curate Dolma. |
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- 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. |
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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)! |
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## Versions |
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At the moment, there are five versions of Dolma available: |
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| **Version** | **Default?** | **Release Date** | **Size** (gzip) | **Description** | |
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|--|:--:|--|--|--| |
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| `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. | |
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| `v1_6-sample` | | 2024-01-31 | 16.4 GB | A smaller sample of Dolma, with roughly 10 billion tokens. Useful for data exploration. | |
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| `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. | |
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| `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) | |
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| `v1` | | 2023-08-18 | 6.0 TB | The first version of Dolma. | |
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(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`.) |
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## Summary Statistics (v1.6) |
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| **Source** | **Doc Type** | **UTF-8 bytes** (GB) | **Documents** (millions) | **Unicode words** (billions) | **Llama tokens** (billions) | |
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|--|--|--|--|--|--| |
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| Common Crawl | web pages | 9,022 | 3,370 | 1,775 | 2,281 | |
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| The Stack | code| 1,043| 210 | 260| 411 | |
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| C4 | web pages | 790 | 364 | 153| 198 | |
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| Reddit| social media| 339 | 377| 72| 89 | |
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| PeS2o | STEM papers| 268 | 38.8| 50| 70 | |
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| Project Gutenberg | books | 20.4 | 0.056 | 4.0 | 6.0 | |
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| Wikipedia, Wikibooks | encyclopedic | 16.2 | 6.2 | 3.7 | 4.3 | |
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| **Total** | | **11,519** | **4,367** | **2,318** | **3,059** | |
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## Download |
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The fastest way to download Dolma is to clone this repository and use the files in the `url` directory. |
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We recommend using wget in parallel mode to download the files. For example: |
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```bash |
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DATA_DIR="<path_to_your_data_directory>" |
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PARALLEL_DOWNLOADS="<number_of_parallel_downloads>" |
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DOLMA_VERSION="<version_of_dolma_to_download>" |
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git clone https://huggingface.co/datasets/allenai/dolma |
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mkdir -p "${DATA_DIR}" |
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cat "dolma/urls/${DOLMA_VERSION}.txt" | xargs -n 1 -P "${PARALLEL_DOWNLOADS}" wget -q -P "$DATA_DIR" |
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``` |
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Then, to load this data using HuggingFace's `datasets` library, you can use the following code: |
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```python |
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import os |
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from datasets import load_dataset |
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os.environ["DATA_DIR"] = "<path_to_your_data_directory>" |
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dataset = load_dataset("allenai/dolma", split="train") |
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``` |
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## Bibtex |
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If you use our dataset or tooling, please cite us at: |
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```bibtex |
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@article{dolma, |
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title = {{Dolma: An Open Corpus of Three Trillion Tokens for Language Model Pretraining Research}}, |
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author = { |
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Luca Soldaini and Rodney Kinney and Akshita Bhagia and Dustin Schwenk and David Atkinson and |
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Russell Authur and Ben Bogin and Khyathi Chandu and Jennifer Dumas and Yanai Elazar and |
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Valentin Hofmann and Ananya Harsh Jha and Sachin Kumar and Li Lucy and Xinxi Lyu and Ian Magnusson and |
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Jacob Morrison and Niklas Muennighoff and Aakanksha Naik and Crystal Nam and Matthew E. Peters and |
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Abhilasha Ravichander and Kyle Richardson and Zejiang Shen and Emma Strubell and Nishant Subramani and |
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Oyvind Tafjord and Evan Pete Walsh and Hannaneh Hajishirzi and Noah A. Smith and Luke Zettlemoyer and |
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Iz Beltagy and Dirk Groeneveld and Jesse Dodge and Kyle Lo |
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}, |
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year = {2024}, |
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journal={arXiv preprint}, |
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} |
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``` |
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