Datasets:
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10B<n<100B
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Rename bertic_data to xlm-r-bertic-data
Browse files
bertic_data.py → xlm-r-bertic-data.py
RENAMED
@@ -24,34 +24,10 @@ _URLS = {
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_HOMEPAGE = _URL
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_DESCRIPTION = """\
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Data used to train
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"""
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_CITATION = r"""
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title = "{BERT}i{\'c} - The Transformer Language Model for {B}osnian, {C}roatian, {M}ontenegrin and {S}erbian",
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author = "Ljube{\v{s}}i{\'c}, Nikola and
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Lauc, Davor",
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editor = "Babych, Bogdan and
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Kanishcheva, Olga and
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Nakov, Preslav and
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Piskorski, Jakub and
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Pivovarova, Lidia and
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Starko, Vasyl and
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Steinberger, Josef and
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Yangarber, Roman and
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Marci{\'n}czuk, Micha{\l} and
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Pollak, Senja and
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P{\v{r}}ib{\'a}{\v{n}}, Pavel and
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Robnik-{\v{S}}ikonja, Marko",
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booktitle = "Proceedings of the 8th Workshop on Balto-Slavic Natural Language Processing",
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month = apr,
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year = "2021",
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address = "Kiyv, Ukraine",
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publisher = "Association for Computational Linguistics",
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url = "https://aclanthology.org/2021.bsnlp-1.5",
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pages = "37--42",
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abstract = "In this paper we describe a transformer model pre-trained on 8 billion tokens of crawled text from the Croatian, Bosnian, Serbian and Montenegrin web domains. We evaluate the transformer model on the tasks of part-of-speech tagging, named-entity-recognition, geo-location prediction and commonsense causal reasoning, showing improvements on all tasks over state-of-the-art models. For commonsense reasoning evaluation we introduce COPA-HR - a translation of the Choice of Plausible Alternatives (COPA) dataset into Croatian. The BERTi{\'c} model is made available for free usage and further task-specific fine-tuning through HuggingFace.",
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}"""
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class BerticData(datasets.GeneratorBasedBuilder):
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_HOMEPAGE = _URL
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_DESCRIPTION = """\
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Data used to train XLM-Roberta-Bertić.
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"""
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_CITATION = r"""
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To be added soon."""
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class BerticData(datasets.GeneratorBasedBuilder):
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