Instructions to use nlp-cimat/politibeto with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nlp-cimat/politibeto with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="nlp-cimat/politibeto")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("nlp-cimat/politibeto") model = AutoModelForMaskedLM.from_pretrained("nlp-cimat/politibeto") - Notebooks
- Google Colab
- Kaggle
PolitiBETO: A Spanish BERT adapted to a language domain of Political Tweets
PolitiBETO is a BERT model tailored for political tasks in social media corpora. It is a Domain Adaptation on top of BETO, a pretrained BERT in Spanish. This model is meant to be fine-tuned for downstream tasks.
Citation
To cite this in a publication please use the following:
@inproceedings{PolitiBeto2022,
title={{NLP-CIMAT} at {P}olitic{E}s 2022: {P}oliti{BETO}, a {D}omain-{A}dapted {T}ransformer for {M}ulti-class {P}olitical {A}uthor {P}rofiling},
author={Emilio Villa-Cueva and Ivan Gonz{\'a}lez-Franco and Fernando Sanchez-Vega and Adri{\'a}n Pastor L{\'o}pez-Monroy},
booktitle={Proceedings of the Iberian Languages Evaluation Forum (IberLEF 2022)},
series = {{CEUR} Workshop Proceedings},
publisher = {CEUR-WS},
year={2022}
}
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