legacy-datasets/wikipedia
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How to use mmaguero/gn-bert-tiny-cased with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("fill-mask", model="mmaguero/gn-bert-tiny-cased") # Load model directly
from transformers import AutoTokenizer, AutoModelForMaskedLM
tokenizer = AutoTokenizer.from_pretrained("mmaguero/gn-bert-tiny-cased")
model = AutoModelForMaskedLM.from_pretrained("mmaguero/gn-bert-tiny-cased")A pre-trained BERT model for Guarani (2 layers, cased). Trained on Wikipedia + Wiktionary (~800K tokens).
@article{aguero-et-al2023multi-affect-low-langs-grn,
title={Multidimensional Affective Analysis for Low-resource Languages: A Use Case with Guarani-Spanish Code-switching Language},
author={Agüero-Torales, Marvin Matías, López-Herrera, Antonio Gabriel, and Vilares, David},
journal={Cognitive Computation},
year={2023},
publisher={Springer},
notes={Forthcoming}
}