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--- |
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tags: |
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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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| **Name** | `it_spacy_ner_trf` | |
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| **Version** | `0.1` | |
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| **spaCy** | `>=3.5.1,<3.6.0` | |
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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** | [tner/wikiann](https://huggingface.co/datasets/tner/wikiann) | |
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| **License** | `MIT` | |
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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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``` |
