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--- |
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language: |
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- en |
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- es |
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- fr |
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- it |
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license: apache-2.0 |
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pretty_name: Multilingual Medical Corpus |
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tags: |
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- medical |
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dataset_info: |
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features: |
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- name: text |
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dtype: string |
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splits: |
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- name: en |
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num_bytes: 7672665166 |
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num_examples: 21226237 |
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- name: es |
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num_bytes: 6245812986 |
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num_examples: 35444286 |
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- name: fr |
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num_bytes: 4763269707 |
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num_examples: 7192779 |
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- name: it |
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num_bytes: 1021535232 |
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num_examples: 3504555 |
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download_size: 10530951092 |
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dataset_size: 19703283091 |
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configs: |
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- config_name: default |
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data_files: |
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- split: en |
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path: data/en-* |
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- split: es |
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path: data/es-* |
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- split: fr |
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path: data/fr-* |
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- split: it |
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path: data/it-* |
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--- |
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|
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<p align="center"> |
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<br> |
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<img src="http://www.ixa.eus/sites/default/files/anitdote.png" style="width: 30%;"> |
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<h2 align="center">Mutilingual Medical Corpus</h2> |
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<be> |
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<p align="justify"> |
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Multilingual-Medical-Corpus a 3 billion word multilingual corpus for training LLMs adapted to the medical domain. Multilingual-Medical-Corpus includes four languages, namely, English, Spanish, French, and Italian. |
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</p> |
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- 📖 Paper: [Medical mT5: An Open-Source Multilingual Text-to-Text LLM for The Medical Domain](https://arxiv.org/abs/2404.07613) |
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- 🌐 Project Website: [https://univ-cotedazur.eu/antidote](https://univ-cotedazur.eu/antidote) |
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# Corpus Description |
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- **Developed by**: Iker García-Ferrero, Rodrigo Agerri, Aitziber Atutxa Salazar, Elena Cabrio, Iker de la Iglesia, Alberto Lavelli, Bernardo Magnini, Benjamin Molinet, Johana Ramirez-Romero, German Rigau, Jose Maria Villa-Gonzalez, Serena Villata and Andrea Zaninello |
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- **Contact**: [Iker García-Ferrero](https://ikergarcia1996.github.io/Iker-Garcia-Ferrero/) and [Rodrigo Agerri](https://ragerri.github.io/) |
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- **Website**: [https://univ-cotedazur.eu/antidote](https://univ-cotedazur.eu/antidote) |
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- **Funding**: CHIST-ERA XAI 2019 call. Antidote (PCI2020-120717-2) funded by MCIN/AEI /10.13039/501100011033 and by European Union NextGenerationEU/PRTR |
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- **Language(s) (NLP)**: English, Spanish, French, Italian |
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- **License**: apache-2.0 |
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<table border="1" cellspacing="0" cellpadding="5"> |
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<caption>Data sources and word counts by language.</caption> |
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<thead> |
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<tr> |
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<th>Language</th> |
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<th>Source</th> |
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<th>Words</th> |
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</tr> |
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</thead> |
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<tbody> |
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<tr> |
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<td rowspan="3">English</td> |
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<td>ClinicalTrials</td> |
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<td>127.4M</td> |
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</tr> |
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<tr> |
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<td>EMEA</td> |
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<td>12M</td> |
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</tr> |
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<tr> |
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<td>PubMed</td> |
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<td>968.4M</td> |
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</tr> |
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<tr> |
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<td rowspan="6">Spanish</td> |
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<td>EMEA</td> |
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<td>13.6M</td> |
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</tr> |
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<tr> |
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<td>PubMed</td> |
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<td>8.4M</td> |
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</tr> |
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<tr> |
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<td>Medical Crawler</td> |
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<td>918M</td> |
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</tr> |
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<tr> |
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<td>SPACC</td> |
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<td>350K</td> |
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</tr> |
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<tr> |
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<td>UFAL</td> |
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<td>10.5M</td> |
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</tr> |
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<tr> |
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<td>WikiMed</td> |
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<td>5.2M</td> |
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</tr> |
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<tr> |
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<td rowspan="5">French</td> |
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<td>PubMed</td> |
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<td>1.4M</td> |
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</tr> |
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<tr> |
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<td>Science Direct</td> |
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<td>15.2M</td> |
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</tr> |
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<tr> |
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<td>Wikipedia - Médecine</td> |
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<td>5M</td> |
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</tr> |
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<tr> |
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<td>EDP</td> |
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<td>48K</td> |
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</tr> |
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<tr> |
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<td>Google Patents</td> |
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<td>654M</td> |
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</tr> |
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<tr> |
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<td rowspan="13">Italian</td> |
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<td>Medical Commoncrawl - IT</td> |
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<td>67M</td> |
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</tr> |
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<tr> |
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<td>Drug instructions</td> |
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<td>30.5M</td> |
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</tr> |
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<tr> |
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<td>Wikipedia - Medicina</td> |
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<td>13.3M</td> |
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</tr> |
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<tr> |
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<td>E3C Corpus - IT</td> |
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<td>11.6M</td> |
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</tr> |
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<tr> |
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<td>Medicine descriptions</td> |
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<td>6.3M</td> |
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</tr> |
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<tr> |
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<td>Medical theses</td> |
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<td>5.8M</td> |
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</tr> |
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<tr> |
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<td>Medical websites</td> |
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<td>4M</td> |
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</tr> |
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<tr> |
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<td>PubMed</td> |
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<td>2.3M</td> |
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</tr> |
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<tr> |
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<td>Supplement description</td> |
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<td>1.3M</td> |
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</tr> |
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<tr> |
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<td>Medical notes</td> |
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<td>975K</td> |
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</tr> |
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<tr> |
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<td>Pathologies</td> |
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<td>157K</td> |
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</tr> |
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<tr> |
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<td>Medical test simulations</td> |
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<td>26K</td> |
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</tr> |
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<tr> |
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<td>Clinical cases</td> |
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<td>20K</td> |
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</tr> |
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</tbody> |
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</table> |
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|
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# Open Source Models trained with Multilingual-Medical-Corpus: |
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<table border="1" cellspacing="0" cellpadding="5"> |
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<thead> |
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<tr> |
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<th></th> |
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<th><a href="https://huggingface.co/HiTZ/Medical-mT5-large">HiTZ/Medical-mT5-large</a></th> |
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<th><a href="https://huggingface.co/HiTZ/Medical-mT5-xl">HiTZ/Medical-mT5-xl</a></th> |
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<th><a href="https://huggingface.co/HiTZ/Medical-mT5-large-multitask">HiTZ/Medical-mT5-large-multitask</a></th> |
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<th><a href="https://huggingface.co/HiTZ/Medical-mT5-xl-multitask">HiTZ/Medical-mT5-xl-multitask</a></th> |
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</tr> |
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</thead> |
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<tbody> |
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<tr> |
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<td>Param. no.</td> |
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<td>738M</td> |
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<td>3B</td> |
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<td>738M</td> |
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<td>3B</td> |
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</tr> |
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<tr> |
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<td>Task</td> |
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<td>Language Modeling</td> |
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<td>Language Modeling</td> |
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<td>Multitask Sequence Labeling</td> |
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<td>Multitask Sequence Labeling</td> |
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</tr> |
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<tr> |
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</tbody> |
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</table> |
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## Citation |
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```bibtext |
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@misc{garcíaferrero2024medical, |
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title={Medical mT5: An Open-Source Multilingual Text-to-Text LLM for The Medical Domain}, |
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author={Iker García-Ferrero and Rodrigo Agerri and Aitziber Atutxa Salazar and Elena Cabrio and Iker de la Iglesia and Alberto Lavelli and Bernardo Magnini and Benjamin Molinet and Johana Ramirez-Romero and German Rigau and Jose Maria Villa-Gonzalez and Serena Villata and Andrea Zaninello}, |
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year={2024}, |
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eprint={2404.07613}, |
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archivePrefix={arXiv}, |
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primaryClass={cs.CL} |
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} |
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``` |