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vabatista/geological-ner
geological-ner is a token classification model from vabatista. Use it when you need labels on individual words, such as names. It is set up for transformers. The card lists the license as mit.
This model is a Brazilian Portuguese Named Entity Recognition (NER), based on neuralmind/bert-base-portuguese-cased base model and specialized in Geological concepts. It was trained for 3 epochs using the dataset from…
Downloads · 30 days
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From the Hugging Face model README
This model is a Brazilian Portuguese Named Entity Recognition (NER), based on neuralmind/bert-base-portuguese-cased base model and specialized in Geological concepts. It was trained for 3 epochs using the dataset from this paper.
You can find the notebook used to train the model here. Trainer output was:

To use this model, run into a pipeline:
## run the prediction
txt = YOUR_TEXT
classifier = pipeline("ner", model=model, tokenizer=tokenizer, aggregation_strategy='simple')
entities = classifier(txt)
## display in a fancy way
dict_ents = {
'text': txt,
'ents': [{'start': ent['start'], 'end': ent['end'], 'label': ent['entity_group']} for ent in entities],
'title': None
}
displacy.render(dict_ents, manual=True, style="ent")