https://github.com/bigscience-workshop/biomedical

Tools for curating biomedical training data for large-scale language modeling

https://github.com/bigscience-workshop/biomedical

Science Score: 33.0%

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    Links to: arxiv.org
  • Committers with academic emails
    5 of 65 committers (7.7%) from academic institutions
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    Low similarity (11.9%) to scientific vocabulary

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transformer audio pretrained-models pytorch-transformers speech-recognition vlm cryptocurrency cryptography jax deepseek
Last synced: 10 months ago · JSON representation

Repository

Tools for curating biomedical training data for large-scale language modeling

Basic Info
  • Host: GitHub
  • Owner: bigscience-workshop
  • Language: Python
  • Default Branch: main
  • Size: 25.5 MB
Statistics
  • Stars: 481
  • Watchers: 30
  • Forks: 117
  • Open Issues: 179
  • Releases: 0
Created almost 5 years ago · Last pushed over 1 year ago
Metadata Files
Readme Contributing Codeowners

README.md

BigBIO: Biomedical Dataset Library

BigBIO (BigScience Biomedical) is an open library of biomedical dataloaders built using Huggingface's (🤗) datasets library for data-centric machine learning.

Our goals include:

  • Lightweight, programmatic access to biomedical datasets at scale
  • Promoting reproducibility in data processing
  • Better documentation for dataset provenance, licensing, and other key attributes
  • Easier generation of meta-datasets for natural language prompting, multi-task learning

Currently BigBIO provides support for:

  • 126+ biomedical datasets
  • 10+ languages
  • 12 task categories
  • Harmonized dataset schemas by task type
  • Metadata on licensing, coarse/fine-grained task types, domain, and more!

How to Use BigBIO

The preferred way to use these datasets is to access them from the Official BigBIO Hub.

Minimally, ensure you have the datasets library installed. Preferably, install the requirements as follows:

pip install -r requirements.txt.


You can access BigBIO datasets as follows:

python from datasets import load_dataset data = load_dataset("bigbio/biosses")

In most cases, scripts load the original schema of the dataset by default. You can also access the BigBIO split that streamlines access to key information in datasets given a particular task.


For example, the biosses dataset follows a pairs based schema, where text-based inputs (sentences, paragraphs) are assigned a "translated" pair.

python from datasets import load_dataset data = load_dataset("bigbio/biosses", name="biosses_bigbio_pairs")

Generally, you can load your datasets as follows:

```python

Load original schema

data = loaddataset("bigbio/<yourdataset>")

Load BigBIO schema

data = loaddataset("bigbio/<yourdatasethere>", name="<yourdataset>bigbio") ```

Check the datacards on the Hub to see what splits are available to you. You can find more information about schemas in Documentation below.

Benchmark Support

BigBIO includes support for almost all datasets included in other popular English biomedical benchmarks.

| Task Type | Dataset | BigBIO (ours) | BLUE | BLURB | BoX | DUA needed | |:---------:|:---------:|:---------:|:---------:|:---------:|:---------:|:---------:| | NER | BC2GM | ✓ | | ✓ | ✓ | | | NER | BC5-chem | ✓ | ✓ | ✓ | ✓ | | | NER | BC5-disease | ✓ | ✓ | ✓ | ✓ | | | NER | EBM PICO | ✓ | | ✓ | | | | NER | JNLPBA | ✓ | | ✓ | ✓ | | | NER | NCBI-disease | ✓ | | ✓ | ✓ | | | RE | ChemProt | ✓ | ✓ | ✓ | ✓ | | | RE | DDI | ✓ | ✓ | ✓ | ✓ | | | RE | GAD | ✓ | | ✓ | | | | QA | PubMedQA | ✓ | | ✓ | ✓ | | | QA | BioASQ | ✓ | | ✓ | ✓ | ✓ | | DC | HoC | ✓ | ✓ | ✓ | ✓ | | | STS | BIOSSES | ✓ | ✓ | ✓ | | | | STS | MedSTS | * | ✓ | | | ✓ | | NER | n2c2 2010 | ✓ | ✓ | | ✓ | ✓ | | NER | ShARe/CLEF 2013 | * | ✓ | | | ✓ | | NLI | MedNLI | ✓ | ✓ | | | ✓ | | NER | n2c2 deid 2006 | ✓ | | | ✓ | ✓ | | DC | n2c2 RFHD 2014 | ✓ | | | ✓ | ✓ | | NER | AnatEM | ✓ | | | ✓ | | | NER | BC4CHEMD | ✓ | | | ✓ | | | NER | BioNLP09 | ✓ | | | ✓ | | | NER | BioNLP11EPI | ✓ | | | ✓ | | | NER | BioNLP11ID | ✓ | | | ✓ | | | NER | BioNLP13CG | ✓ | | | ✓ | | | NER | BioNLP13GE | ✓ | | | ✓ | | | NER | BioNLP13PC | ✓ | | | ✓ | | | NER | CRAFT | * | | | ✓ | | | NER | Ex-PTM | ✓ | | | ✓ | | | NER | Linnaeus | ✓ | | | ✓ | | | POS | GENIA | * | | | ✓ | | | SA | Medical Drugs | ✓ | | | ✓ | | | SR | COVID | | | | private | | | SR | Cooking | | | | private | | | SR | HRT | | | | private | | | SR | Accelerometer | | | | private | | | SR | Acromegaly | | | | private | |

* denotes dataset implementation in-progress

Documentation

Tutorials

TBA - Links may not be applicable yet!

Contributing

BigBIO is an open source project - your involvement is warmly welcome! If you're excited to join us, we recommend the following steps:

  • Looking for ideas? See our Volunteer Project Board to see what we may need help with.

  • Have your own idea? Contact an admin in the form of an issue.

  • Implement your idea following guidelines set by the official contributing guide

  • Wait for admin approval; approval is iterative, but if accepted will belong to the main repository.

Currently, only admins will be merging all accepted changes to the Hub.

Feel free to join our Discord!

Citing

If you use BigBIO in your work, please cite

@article{fries2022bigbio, title = { BigBIO: A Framework for Data-Centric Biomedical Natural Language Processing }, author = { Fries, Jason Alan and Weber, Leon and Seelam, Natasha and Altay, Gabriel and Datta, Debajyoti and Garda, Samuele and Kang, Myungsun and Su, Ruisi and Kusa, Wojciech and Cahyawijaya, Samuel and others }, journal = {arXiv preprint arXiv:2206.15076}, year = 2022 }

Acknowledgements

BigBIO is a open source, community effort made possible through the efforts of many volunteers as part of BigScience and the Biomedical Hackathon.

Owner

  • Name: BigScience Workshop
  • Login: bigscience-workshop
  • Kind: organization
  • Email: bigscience-contact@googlegroups.com

Research workshop on large language models - The Summer of Language Models 21

GitHub Events

Total
  • Issues event: 17
  • Watch event: 29
  • Issue comment event: 23
  • Push event: 10
  • Pull request review comment event: 21
  • Pull request event: 14
  • Pull request review event: 23
  • Fork event: 4
Last Year
  • Issues event: 17
  • Watch event: 29
  • Issue comment event: 23
  • Push event: 10
  • Pull request review comment event: 21
  • Pull request event: 14
  • Pull request review event: 23
  • Fork event: 4

Committers

Last synced: about 1 year ago

All Time
  • Total Commits: 705
  • Total Committers: 65
  • Avg Commits per committer: 10.846
  • Development Distribution Score (DDS): 0.723
Past Year
  • Commits: 24
  • Committers: 15
  • Avg Commits per committer: 1.6
  • Development Distribution Score (DDS): 0.75
Top Committers
Name Email Commits
Gabriel Altay g****y@g****m 195
Natasha Seelam n****1@g****m 87
Leon Weber l****r 73
sg-wbi 8****i 43
Jason Alan Fries j****s@s****u 34
Myungsun Kang s****g@M****l 29
Simon Ott s****t@g****t 25
debajyotidatta d****2@g****m 15
barthfab 8****b 13
Mario Sänger 4****r 13
GullyBurns g****s@c****m 11
Wojciech Kusa W****a 11
Myungsun Kang s****g@m****n 11
Florian Borchert f****t@g****m 8
Shamik Bose 5****e 7
Samuel Cahyawijaya S****a@g****m 6
Rosaline Su r****u@g****m 6
nachollorca m****p@g****m 6
John Giorgi j****i@g****m 6
Daniel León Periñán d****l@i****m 4
Albert Villanova del Moral 8****a 4
Ayush Singh s****y 4
Labrak Yanis y****k@a****r 4
Robert Martin m****o@i****e 4
karthikrangasai 3****i 4
Stephen Bach s****h@g****m 4
j-chim j****m@g****m 4
théo gigant 7****o 4
Marianna Nezhurina 4****3 3
Marc Pàmies m****7@g****m 3
and 35 more...

Issues and Pull Requests

Last synced: 11 months ago

All Time
  • Total issues: 48
  • Total pull requests: 54
  • Average time to close issues: 10 months
  • Average time to close pull requests: 9 months
  • Total issue authors: 18
  • Total pull request authors: 23
  • Average comments per issue: 0.79
  • Average comments per pull request: 1.8
  • Merged pull requests: 38
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 18
  • Pull requests: 5
  • Average time to close issues: about 1 month
  • Average time to close pull requests: 11 days
  • Issue authors: 3
  • Pull request authors: 3
  • Average comments per issue: 0.17
  • Average comments per pull request: 0.2
  • Merged pull requests: 4
  • Bot issues: 0
  • Bot pull requests: 0
Top Authors
Issue Authors
  • mariosaenger (17)
  • phlobo (4)
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  • nachollorca (4)
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  • drAbreu (1)
  • galtay (1)
  • Miking98 (1)
Pull Request Authors
  • phlobo (11)
  • shamikbose (7)
  • karthikrangasai (6)
  • napsternxg (6)
  • leonweber (6)
  • mariosaenger (5)
  • raissinging (4)
  • GullyBurns (4)
  • davidkartchner (4)
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  • simonada (3)
  • nachollorca (3)
  • kai-car (2)
  • mcullan (2)
  • WangXII (2)
Top Labels
Issue Labels
bug (9) CoNLL (2) NER (2) New Dataset (1) High (1) CC BY 3.0 (1) English (1) Coreference (1) CC BY SA (1) Romanian (1)
Pull Request Labels
local dataset (1)

Dependencies

dev-requirements.txt pypi
  • bioc ==2.0.post4 development
  • black >=22.1.0,<22.2.0 development
  • datasets >=2.8.0,<3.0.0 development
  • flake8 >=3.8.3,<3.9.0 development
  • isort >=5.0.0,<5.1.0 development
  • numpy >=1.21.2 development
  • openpyxl >=3.0.9,<3.1.0 development
  • pandas >=1.3.3 development
requirements.txt pypi
  • bioc ==2.0.post4
  • datasets >=2.8.0,<3.0.0
  • numpy >=1.21.2
  • openpyxl >=3.0.9,<3.1.0
  • pandas >=1.3.3
.github/workflows/selfassign.yml actions
pyproject.toml pypi
setup.py pypi