---
tags:
- spacy
language:
- it
license: mit
datasets:
- wikiann
library_name: spacy
pipeline_tag: token-classification
---
| 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](https://huggingface.co/datasets/tner/wikiann) |
| **License** | `MIT` |
| **Author** | [Nicola Procopio](https://github.com/nickprock) |

---

# Description

SpaCy version of [nickprock/bert-italian-finetuned-ner](https://huggingface.co/nickprock/bert-italian-finetuned-ner).

> The original model is wrapped by [spacy-wrap](https://github.com/KennethEnevoldsen/spacy-wrap)

## Use it in SpaCy

```
!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_)

```