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README.md
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<details>
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<summary>Click to expand</summary>
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- [Model
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- [Intended Uses and
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- [How to Use](#how-to-use)
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- [Limitations and bias](#limitations-and-bias)
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- [Training](#training)
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- [Evaluation](#evaluation)
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- [Additional
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- [Author](#author)
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- [Contact
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- [Copyright](#copyright)
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- [Licensing
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- [Funding](#funding)
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- [Citation
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- [Disclaimer](#disclaimer)
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</details>
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## Model description
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Biomedical pretrained language model for Spanish. This model is a [RoBERTa-based](https://github.com/pytorch/fairseq/tree/master/examples/roberta) model trained on a **biomedical-clinical** corpus in Spanish collected from several sources.
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## Intended uses
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The model is ready-to-use only for masked language modelling to perform the Fill Mask task (try the inference API or read the next section). However, it is intended to be fine-tuned on downstream tasks such as Named Entity Recognition or Text Classification.
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## How to use
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### Author
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Text Mining Unit (TeMU) at the Barcelona Supercomputing Center (bsc-temu@bsc.es)
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### Contact
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For further information, send an email to <plantl-gob-es@bsc.es>
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### Copyright
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### Funding
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This work was funded by the Spanish State Secretariat for Digitalization and Artificial Intelligence (SEDIA) within the framework of the Plan-TL.
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### Citation
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If you use our models, please cite our latest preprint:
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```bibtex
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<details>
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<summary>Click to expand</summary>
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+
- [Model description](#model-description)
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+
- [Intended Uses and limitations](#intended-use)
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- [How to Use](#how-to-use)
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- [Limitations and bias](#limitations-and-bias)
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- [Training](#training)
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- [Evaluation](#evaluation)
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| 30 |
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- [Additional information](#additional-information)
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- [Author](#author)
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- [Contact information](#contact-information)
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- [Copyright](#copyright)
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+
- [Licensing information](#licensing-information)
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- [Funding](#funding)
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- [Citation information](#citation-information)
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- [Disclaimer](#disclaimer)
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</details>
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## Model description
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Biomedical pretrained language model for Spanish. This model is a [RoBERTa-based](https://github.com/pytorch/fairseq/tree/master/examples/roberta) model trained on a **biomedical-clinical** corpus in Spanish collected from several sources.
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## Intended uses and limitations
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The model is ready-to-use only for masked language modelling to perform the Fill Mask task (try the inference API or read the next section). However, it is intended to be fine-tuned on downstream tasks such as Named Entity Recognition or Text Classification.
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## How to use
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### Author
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Text Mining Unit (TeMU) at the Barcelona Supercomputing Center (bsc-temu@bsc.es)
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### Contact information
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For further information, send an email to <plantl-gob-es@bsc.es>
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### Copyright
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### Funding
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This work was funded by the Spanish State Secretariat for Digitalization and Artificial Intelligence (SEDIA) within the framework of the Plan-TL.
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### Citation information
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If you use our models, please cite our latest preprint:
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```bibtex
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