README.md

---
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:

- Read Dolma **announcement blogpost** [on Medium](https://soldni.medium.com/dolma-3-trillion-tokens-open-llm-corpus-9a0ff4b8da64);
- Learn more about Dolma on its [**Data Sheet**](https://drive.google.com/file/d/12gOf5I5RytsD159nSP7iim_5zN31FCXq/view?usp=drive_link);
- 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)!

## Summary Statistics


|**Source**|**Type**|**Gzip files (GB)**|**Documents (millions)**|**[GPT-NeoX](https://huggingface.co/EleutherAI/gpt-neox-20b) Tokens (billions)**|
|:---|:---:|:---:|:---:|:----:|
|[CommonCrawl](https://commoncrawl.org/)|web|4,197|4,600|2,415|
|[C4](https://huggingface.co/datasets/allenai/c4)|web|302|364|175|
|[peS2o](https://huggingface.co/datasets/allenai/peS2o)|academic|150|38.8|57|
|[The Stack](https://huggingface.co/datasets/bigcode/the-stack)|code|319|236|430|
|[Project Gutenberg](https://www.gutenberg.org/)|books|6.6|0.052|4.8|
|[Wikipedia](https://dumps.wikimedia.org/)|encyclopedic|5.8|6.1|3.6|
||**Total** |**4980.4**|**5,245**|**3,084**|


## Download


The fastest way to download Dolma is to directly download the individual files across multiple threads.
This can be achieved using wget or [aria2](https://github.com/aria2/aria2) Linux/Mac/Windows package (`sudo apt-get install aria2` on Ubuntu).

For downloading individual files, simply use `wget` as follows:

`wget --header 'Authorization: Bearer YOUR_HF_HUB_ACCESS_TOKEN' https://huggingface.co/datasets/allenai/dolma/resolve/main/data/peS2o/s2_v3-0000.json.gz`

For downloading many files across multiple threads, first prepare a `.txt` file with the urls you would like such as via the script below:

```python
OUT_DIRECTORY = "/scratch/dolma/data"

# URLs for cc_en_head
cc_en_head_base_url = "https://huggingface.co/datasets/allenai/dolma/resolve/main/data/common-crawl/cc_en_head/cc_en_head-"
cc_en_head_url_list = [f"{cc_en_head_base_url}{str(i).zfill(4)}.json.gz\n  dir={OUT_DIRECTORY}/cc_en_head\n  out=cc_en_head-{str(i).zfill(4)}.json.gz" for i in range(612)]

# URLs for cc_en_middle
cc_en_middle_base_url = "https://huggingface.co/datasets/allenai/dolma/resolve/main/data/common-crawl/cc_en_middle/cc_en_middle-"
cc_en_middle_url_list = [f"{cc_en_middle_base_url}{str(i).zfill(4)}.json.gz\n  dir={OUT_DIRECTORY}/cc_en_middle\n  out=cc_en_middle-{str(i).zfill(4)}.json.gz" for i in range(777)]

# URLs for cc_en_tail
cc_en_tail_base_url = "https://huggingface.co/datasets/allenai/dolma/resolve/main/data/common-crawl/cc_en_tail/cc_en_tail-"
cc_en_tail_url_list = [f"{cc_en_tail_base_url}{str(i).zfill(4)}.json.gz\n  dir={OUT_DIRECTORY}/cc_en_tail\n  out=cc_en_tail-{str(i).zfill(4)}.json.gz" for i in range(1493)]

# URLs for s2_v3
s2_v3_base_url = "https://huggingface.co/datasets/allenai/dolma/resolve/main/data/peS2o/s2_v3-"
s2_v3_url_list = [f"{s2_v3_base_url}{str(i).zfill(4)}.json.gz\n  dir={OUT_DIRECTORY}/peS2o\n  out=s2_v3-{str(i).zfill(4)}.json.gz" for i in range(42)]

# URLs for The Stack
LANG_TO_FILES = {'lasso': 1, 'nsis': 1, 'literate-agda': 1, 'metal': 1, 'xojo': 1, 'max': 8, 'jupyter-notebook': 101, 'asp': 7, 'elixir': 14, 'html+erb': 19, 'julia': 22, 'dart': 63, 'ragel-in-ruby-host': 1, 'api-blueprint': 1, 'gams': 1, 'tex': 71, 'xml': 101, 'smalltalk': 17, 'cmake': 11, 'piglatin': 1, "cap'n-proto": 1, 'common-lisp': 21, 'stylus': 3, 'typescript': 101, 'jflex': 1, 'factor': 1, 'arc': 1, 'parrot-internal-representation': 1, 'aspectj': 1, 'go': 101, 'urweb': 1, 'dns-zone': 1, 'purebasic': 1, 'toml': 15, 'erlang': 11, 'hy': 1, 'component-pascal': 2, 'oz': 1, 'opa': 1, 'handlebars': 10, 'gas': 15, 'less': 17, 'gnuplot': 15, 'harbour': 1, 'vhdl': 16, 'octave': 1, 'powershell': 21, 'clips': 1, 'fish': 1, 'prolog': 1, 'sparql': 1, 'objective-j': 1, 'scaml': 1, 'twig': 20, 'gettext-catalog': 101, 'purescript': 2, 'vala': 1, 'gosu': 1, 'apacheconf': 1, 'xc': 1, 'lean': 3, 'mako': 1, 'r': 4, 'unrealscript': 1, 'solidity': 21, 'pike': 1, 'cartocss': 1, 'maple': 1, 'graphql': 3, 'unity3d-asset': 101, 'swift': 101, 'dockerfile': 13, 'digital-command-language': 1, 'scala': 83, 'sqf': 2, 'logtalk': 1, 'coq': 1, 'shellsession': 1, 'befunge': 1, 'nu': 1, 'ecere-projects': 1, 'zimpl': 1, 'shen': 1, 'golo': 1, 'web-ontology-language': 12, 'sas': 2, 'uno': 1, 'livescript': 1, 'literate-haskell': 1, 'clojure': 8, 'perl6': 1, 'zig': 3, 'liquid': 2, 'ec': 1, 'blitzbasic': 1, 'sql': 101, 'http': 2, 'xproc': 1, 'kit': 1, 'textile': 1, 'netlinx': 1, 'propeller-spin': 1, 'cython': 5, 'realbasic': 1, 'dogescript': 1, 'llvm': 9, 'pawn': 1, 'groff': 40, 'html+django': 3, 'csound': 1, 'd': 1, 'agda': 2, 'css': 101, 'yacc': 7, 'robotframework': 1, 'kotlin': 101, 'grace': 1, 'abap': 2, 'blitzmax': 1, 'webassembly': 3, 'ampl': 1, 'postscript': 16, 'nit': 1, 'gentoo-eclass': 1, 'xpages': 1, 'linker-script': 2, 'yang': 3, 'jade': 4, 'standard-ml': 6, 'javascript': 101, 'moonscript': 1, 'mtml': 1, 'saltstack': 1, 'freemarker': 5, 'ston': 1, 'html+eex': 1, 'xs': 1, 'c++': 101, 'matlab': 1, 'm4': 2, 'xbase': 1, 'perl': 37, 'emacs-lisp': 7, 'bison': 1, 'slim': 2, 'grammatical-framework': 1, 'rdoc': 1, 'nix': 10, 'clean': 1, 'module-management-system': 1, 'nimrod': 6, 'raml': 1, 'forth': 1, 'squirrel': 1, 'alloy': 1, 'opencl': 3, 'c': 101, 'sass': 4, 'eiffel': 2, 'papyrus': 1, 'html': 109, 'java': 101, 'hcl': 14, 'isabelle': 2, 'markdown': 101, 'gentoo-ebuild': 2, 'objdump': 1, 'emberscript': 1, 'text': 101, 'bro': 1, 'opal': 1, 'haskell': 35, 'mupad': 1, 'desktop': 1, 'modelica': 2, 'coldfusion-cfc': 2, 'fantom': 1, 'glsl': 10, 'ocaml': 16, 'nesc': 2, 'scheme': 7, 'crystal': 5, 'tcsh': 1, 'c2hs-haskell': 1, 'idris': 1, 'logos': 4, 'coffeescript': 13, 'g-code': 10, 'sage': 1, 'haml': 4, 'tcl': 7, 'smt': 5, 'ox': 1, 'chuck': 1, 'xquery': 1, 'batchfile': 7, 'pod': 2, 'xtend': 1, 'restructuredtext': 61, 'rmarkdown': 1, 'turtle': 33, 'jsx': 45, 'protocol-buffer': 8, "ren'py": 2, 'diff': 32, 'slash': 1, 'darcs-patch': 1, 'numpy': 1, 'augeas': 1, 'wisp': 1, 'edn': 15, 'ooc': 1, 'bitbake': 2, 'labview': 1, 'inform-7': 1, 'rust': 101, 'creole': 1, 'apl': 1, 'arduino': 11, 'openscad': 2, 'cuda': 9, 'thrift': 1, 'yaml': 101, 'fancy': 1, 'coldfusion': 1, 'python': 101, 'clarion': 1, 'glyph': 1, 'parrot': 1, 'lookml': 1, 'java-server-pages': 19, 'oxygene': 1, 'flux': 1, 'scilab': 1, 'groovy-server-pages': 2, 'rhtml': 1, 'eagle': 52, 'parrot-assembly': 1, 'igor-pro': 1, 'webidl': 1, 'bluespec': 1, 'unified-parallel-c': 1, 'smali': 38, 'haxe': 9, 'ada': 7, 'lua': 48, 'pascal': 21, 'html+php': 6, 'irc-log': 1, 'x10': 1, 'netlogo': 1, 'ioke': 1, 'dm': 1, 'self': 1, 'elm': 5, 'ats': 1, 'brainfuck': 1, 'mask': 1, 'rouge': 1, 'turing': 1, 'lex': 2, 'gap': 1, 'pogoscript': 1, 'kicad': 30, 'io': 1, 'objective-c++': 8, 'qml': 4, 'redcode': 1, 'autoit': 2, 'processing': 4, 'systemverilog': 6, 'gdscript': 5, 'f-sharp': 12, 'fortran': 23, 'monkey': 1, 'c-sharp': 101, 'xslt': 9, 'viml': 6, 'renderscript': 1, 'scss': 84, 'cucumber': 4, 'verilog': 1, 'genshi': 1, 'racket': 1, 'krl': 1, 'actionscript': 10, 'pan': 1, 'cirru': 1, 'chapel': 1, 'pure-data': 2, 'm': 1, 'applescript': 1, 'inno-setup': 1, 'volt': 1, 'myghty': 1, 'groovy': 17, 'ags-script': 1, 'mirah': 1, 'lsl': 1, 'brightscript': 1, 'python-traceback': 1, 'sourcepawn': 2, 'maxscript': 1, 'zephir': 1, 'supercollider': 1, 'mathematica': 20, 'awk': 1, 'autohotkey': 2, 'lfe': 1, 'ruby': 101, 'visual-basic': 20, 'ini': 59, 'red': 1, 'omgrofl': 1, 'idl': 1, 'rebol': 1, 'vue': 101, 'ninja': 2, 'ecl': 1, 'lolcode': 1, 'tea': 1, 'txl': 1, 'smarty': 9, 'vcl': 1, 'php': 101, 'literate-coffeescript': 1, 'click': 1, 'pony': 1, 'mediawiki': 5, 'stata': 5, 'stan': 1, 'nginx': 1, 'asciidoc': 16, 'antlr': 1, 'cobol': 1, 'org': 5, 'latte': 1, 'makefile': 32, 'ceylon': 1, 'graphviz-(dot)': 13, 'lilypond': 1, 'dylan': 1, 'qmake': 1, 'muf': 1, 'j': 1, 'pov-ray-sdl': 1, 'jasmin': 1, 'shell': 73, 'cycript': 1, 'boo': 1, 'hlsl': 2}
stack_base_url = "https://huggingface.co/datasets/allenai/dolma/resolve/main/data/stack-code/"
stack_url_list = []
for lang, num_files in sorted(LANG_TO_FILES.items()):
    for i in range(num_files):
        stack_url_list.append(f"{stack_base_url}{lang}/v3-{str(i).zfill(4)}.json.gz\n  dir={OUT_DIRECTORY}/stack-code/{lang}\n  out=v3-{str(i).zfill(4)}.json.gz")

# Combine all URL lists
all_url_list = cc_en_head_url_list + cc_en_middle_url_list + cc_en_tail_url_list + s2_v3_url_list + stack_url_list

out = open("files.txt", "a")
# Print the combined list of URLs
for i, url in enumerate(all_url_list):
    out.write(url + "\n")
```

Then you can download them all in parallel using:

`aria2c --input-file files.txt --header 'Authorization: Bearer YOUR_HF_HUB_ACCESS_TOKEN'`

You can also add `-s` to increase the number of connections, e.g. `-s 10` (defaults to 5).



To get the exact file counts that are used for The Stack in the above script (`LANG_TO_FILES`), you can follow the below:

Fetch all files (does not download them, so should be fast): `GIT_LFS_SKIP_SMUDGE=1 git clone [email protected]:datasets/allenai/dolma.git`
Then run:
```python
import os

directory = "dolma/data/stack-code"
folder_dict = {}

for folder in os.listdir(directory):
    folder_path = os.path.join(directory, folder)
    if os.path.isdir(folder_path):
        file_count = len([f for f in os.listdir(folder_path) if os.path.isfile(os.path.join(folder_path, f))])
        folder_dict[folder] = file_count

print(folder_dict)
```

## 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 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},
}
```