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README.md
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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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- 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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# Description
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SpaCy version of [nickprock/bert-italian-finetuned-ner](https://huggingface.co/nickprock/bert-italian-finetuned-ner).
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> The original model is wrapped by [spacy-wrap](https://github.com/KennethEnevoldsen/spacy-wrap)
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## Use it in SpaCy
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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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import spacy
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nlp = spacy.load("it_spacy_ner_trf")
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doc = nlp("Domenica andrò allo stadio con Giovanna a guardare la Fiorentina.")
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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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