This checkpoint has been trained for the NER task using the CoNLL2002-es dataset.
This is a NER checkpoint created from
Bertin Gaussian 512
, which is a
RoBERTa-base
model trained from scratch in Spanish. Information on this base model may be found at
its own card
and at deeper detail on
the main project card
.
The training dataset for the base model is
mc4
subsampling documents to a total of about 50 million examples. Sampling is biased towards average perplexity values (using a Gaussian function), discarding more often documents with very large values (poor quality) of very small values (short, repetitive texts).
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bertin-project bertin-base-ner-conll2002-es online free url in huggingface.co:
bertin-base-ner-conll2002-es is an open source model from GitHub that offers a free installation service, and any user can find bertin-base-ner-conll2002-es on GitHub to install. At the same time, huggingface.co provides the effect of bertin-base-ner-conll2002-es install, users can directly use bertin-base-ner-conll2002-es installed effect in huggingface.co for debugging and trial. It also supports api for free installation.
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