Datasets:
v1_7 update
#28
by
kylel
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- .gitignore +1 -1
- README.md +32 -5
- dolma.py +5 -2
- urls/.DS_Store +0 -0
- urls/v1_7.txt +0 -0
.gitignore
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*.so
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# macOS metadata
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# ignoring test output
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/tests/work/
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*.so
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# macOS metadata
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*.DS_Store
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# ignoring test output
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/tests/work/
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README.md
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---
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license: odc-by
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viewer:
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task_categories:
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- text-generation
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language:
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@@ -28,26 +28,51 @@ More information:
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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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**2024-04-15: License Change.** We have updated the license of Dolma to [ODC-BY](https://opendatacommons.org/licenses/by/1-0/). Please see this [blog post](https://blog.allenai.org/making-a-switch-dolma-moves-to-odc-by-8f0e73852f44) for more information.
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## Versions
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At the moment, there are
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| **Version** | **Default?** | **Release Date** | **Size** (gzip) | **Description** |
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|--|:--:|--|--|--|
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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.
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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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| **Total** | | **11,519** | **4,367** | **2,318** | **3,059** |
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## Download
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---
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license: odc-by
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viewer: false
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task_categories:
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- text-generation
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language:
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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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**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](https://huggingface.co/allenai/OLMo-7b-v1.7) model.
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**2024-04-15: License Change.** We have updated the license of Dolma to [ODC-BY](https://opendatacommons.org/licenses/by/1-0/). Please see this [blog post](https://blog.allenai.org/making-a-switch-dolma-moves-to-odc-by-8f0e73852f44) for more information.
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## Versions
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At the moment, there are six versions of Dolma available:
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| **Version** | **Default?** | **Release Date** | **Size** (gzip) | **Description** |
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|--|:--:|--|--|--|
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| `v1_7` | ✅ | 2024-04-15 | 4.5 TB | Used to train [OLMo-7B-v1.7](https://huggingface.co/allenai/OLMo-7b-v1.7). |
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| `v1_6` | | 2024-01-31 | 5.4 TB | An update to v1.5 with some bug-fixes. |
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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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## Summary Statistics (v1.7)
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| **Source** | **Provenance** | **New?** | **Documents** (millions) | **OLMo tokens** (billions) | **Sample Proportion** | **Cutoff Date** | **Processing**
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| Dolma's CC | [Common Crawl](https://commoncrawl.org/) via Dolma v1.6 | Updated | 875.2 | 1,195.5 | 50% | Mar 2023 | Extracted using the Dolma pipeline; new quality filtering and deduplication steps. |
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| Refined Web | [Refined Web](https://huggingface.co/datasets/tiiuae/falcon-refinedweb) | Yes | 664.0 | 456.4 | 100% | Feb 2023 | Filtered using the Dolma pipeline; new quality filtering and deduplication steps. |
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| StarCoder | [StarCoder](https://huggingface.co/blog/starcoder) | Yes | 206.6 | 263.8 | 100% | May 2023 | No further processing. |
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| C4 | [C4](https://huggingface.co/datasets/c4) via Dolma v1.6 | Updated | 249.9 | 138.4 | 50% | Apr 2019 | Filtered using the Dolma pipeline; new quality filtering and deduplication steps. |
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| Reddit | [PushShift API](https://github.com/pushshift/api) | Updated | 377.4 | 79.9 | 100% | Mar 2023 | Extracted using the Dolma pipeline; new quality filtering and deduplication steps. |
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| Semantic Scholar ([S2ORC](https://aclanthology.org/2020.acl-main.447/) & [S2AG](https://www.semanticscholar.org/product/api)) | [peS2o](https://huggingface.co/datasets/allenai/peS2o) via Dolma v1.6 | No | 38.8 | 57.2 | 100% | Mar 2023 | Same as Dolma v1.6 |
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| arXiv | [RedPajama v1](https://huggingface.co/datasets/togethercomputer/RedPajama-Data-1T) | Yes | 1.5 | 28.0 | 100% | Mar 2023 | No further processing. |
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| StackExchange | [RedPajama v1](https://huggingface.co/datasets/togethercomputer/RedPajama-Data-1T) | Yes | 29.3 | 19.6 | 100% | Mar 2023 | No further processing. |
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| Flan | [Flan](https://arxiv.org/abs/2301.13688) via [Tulu](https://huggingface.co/datasets/allenai/tulu-v2-sft-mixture) | Yes | 52.1 | 16.5 | 100% | Mar 2023 | |
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| CC News | [Common Crawl](https://commoncrawl.org/blog/news-dataset-available) | Yes | 22.0 | 14.3 | 100% | Mar 2023 | Extracted using the Dolma pipeline; new quality filtering and deduplication steps. |
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| OpenWebMath | [OpenWebMath](https://huggingface.co/datasets/open-web-math/open-web-math) via [Proof Pile II](https://huggingface.co/datasets/EleutherAI/proof-pile-2) | Yes | 2.9 | 12.6 | 100% | Oct 2023 | Training subset; no further processing. |
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| Algebraic Stack | [Proof Pile II](https://huggingface.co/datasets/EleutherAI/proof-pile-2) | Yes | 2.8 | 12.6 | 100% | Oct 2023 | Training subset; no further processing. |
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| Project Gutenberg | [Project Gutenberg](https://www.gutenberg.org) via Dolma v1.6 | No | 0.0556 | 5.3 | 100% | Mar 2023 | Same as Dolma v1.6 |
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| MegaWika | [MetaWika](https://huggingface.co/datasets/hltcoe/megawika) | Yes | 3.2 | 4.6 | 100% | Jul 2023 | English web pages cited from Wikipedia; curated using the full Dolma pipeline. |
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| Wikipedia & Wikibooks | [Wikimedia](https://dumps.wikimedia.org) via Dolma v1.6 | No | 6.2 | 3.7 | 200% | Mar 2023 | Same as Dolma v1.6 |
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| **Total** | | | | **2,308.5** | **1,715.1** | | |
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(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.)
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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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| **Total** | | **11,519** | **4,367** | **2,318** | **3,059** |
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(Size difference between `v1_6` and `v1_5` is due to different set of metadata included in files: we removed redundant metadata in `v1_6`.)
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## Download
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dolma.py
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# Copyright
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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"v1_5-sample": "urls/v1_5-sample.txt",
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"v1_6": "urls/v1_6.txt",
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"v1_6-sample": "urls/v1_6-sample.txt",
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}
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_VERSIONS = {
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"v1": "1.0.0",
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"v1_5-sample": "1.5.0",
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"v1_6": "1.6.0",
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"v1_6-sample": "1.6.0",
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}
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_DATES = {
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"v1": "(Aug 2023)",
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"v1_5-sample": "(Oct 2023)",
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"v1_6": "(Jan 2024)",
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"v1_6-sample": "(Jan 2024)",
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}
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_BASE_URL = "https://olmo-data.org"
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for name in _URL_LISTS.keys()
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]
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DEFAULT_CONFIG_NAME = "
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def _info(self):
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return datasets.DatasetInfo(
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# Copyright 2024 Allen Institute for AI
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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"v1_5-sample": "urls/v1_5-sample.txt",
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"v1_6": "urls/v1_6.txt",
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"v1_6-sample": "urls/v1_6-sample.txt",
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"v1_7": "urls/v1_7.txt",
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}
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_VERSIONS = {
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"v1": "1.0.0",
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"v1_5-sample": "1.5.0",
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"v1_6": "1.6.0",
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"v1_6-sample": "1.6.0",
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"v1_7": "1.7.0",
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}
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_DATES = {
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"v1": "(Aug 2023)",
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"v1_5-sample": "(Oct 2023)",
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"v1_6": "(Jan 2024)",
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"v1_6-sample": "(Jan 2024)",
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"v1_7": "(Apr 2024)",
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}
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_BASE_URL = "https://olmo-data.org"
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for name in _URL_LISTS.keys()
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]
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DEFAULT_CONFIG_NAME = "v1_7"
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def _info(self):
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return datasets.DatasetInfo(
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urls/.DS_Store
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urls/v1_7.txt
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