unimelb-nlp/wikiann
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How to use nickprock/it_spacy_ner_trf with spaCy:
!pip install https://huggingface.co/nickprock/it_spacy_ner_trf/resolve/main/it_spacy_ner_trf-any-py3-none-any.whl
# Using spacy.load().
import spacy
nlp = spacy.load("it_spacy_ner_trf")
# Importing as module.
import it_spacy_ner_trf
nlp = it_spacy_ner_trf.load()| Feature | Description |
|---|---|
| Name | it_spacy_ner_trf |
| Version | 0.1 |
| spaCy | >=3.5.1,<3.6.0 |
| Default Pipeline | token_classification_transformer |
| Components | token_classification_transformer |
| Vectors | 0 keys, 0 unique vectors (0 dimensions) |
| Sources | tner/wikiann |
| License | MIT |
| Author | Nicola Procopio |
SpaCy version of nickprock/bert-italian-finetuned-ner.
The original model is wrapped by spacy-wrap
!pip install https://huggingface.co/nickprock/it_spacy_ner_trf/resolve/main/it_spacy_ner_trf-any-py3-none-any.whl
import spacy
nlp = spacy.load("it_spacy_ner_trf")
doc = nlp("Domenica andrò allo stadio con Giovanna a guardare la Fiorentina.")
for ent in doc.ents:
print(ent.text, ent.label_)