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  - spacy
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  language:
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  - it
 
 
 
 
 
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  ---
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  | Feature | Description |
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  | --- | --- |
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  | **Default Pipeline** | `token_classification_transformer` |
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  | **Components** | `token_classification_transformer` |
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  | **Vectors** | 0 keys, 0 unique vectors (0 dimensions) |
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- | **Sources** | n/a |
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- | **License** | n/a |
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- | **Author** | [n/a]() |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  - spacy
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  language:
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  - it
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+ license: mit
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+ datasets:
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+ - wikiann
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+ library_name: spacy
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+ pipeline_tag: token-classification
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  ---
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  | Feature | Description |
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  | --- | --- |
 
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  | **Default Pipeline** | `token_classification_transformer` |
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  | **Components** | `token_classification_transformer` |
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  | **Vectors** | 0 keys, 0 unique vectors (0 dimensions) |
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+ | **Author** | [Nicola Procopio](https://github.com/nickprock) |
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+
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+ ---
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+
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+ # Description
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+
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+ SpaCy version of [nickprock/bert-italian-finetuned-ner](https://huggingface.co/nickprock/bert-italian-finetuned-ner).
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+
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+ > The original model is wrapped by [spacy-wrap](https://github.com/KennethEnevoldsen/spacy-wrap)
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+
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+ ## Use it in SpaCy
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+
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+ ```
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+ !pip install https://huggingface.co/nickprock/it_spacy_ner_trf/resolve/main/it_spacy_ner_trf-any-py3-none-any.whl
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+
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+ import spacy
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+ nlp = spacy.load("it_spacy_ner_trf")
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+
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+ doc = nlp("Domenica andrò allo stadio con Giovanna a guardare la Fiorentina.")
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+
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+ for ent in doc.ents:
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+ print(ent.text, ent.label_)
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+
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+ ```