File size: 836 Bytes
038c219 9b71a49 914ff64 9b71a49 6a04f01 914ff64 4508aef 038c219 8f49c81 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 |
---
language:
- es
license: isc
library_name: flair
tags:
- flair
- token-classification
metrics:
- f1
- precision
- recall
- accuracy
widget:
- text: "Jean Paul Gaultier Classique - 50 ML Eau de Parfum Damen Parfum"
---
### Demo: How to use in Flair
Requires:
- **[Flair](https://github.com/flairNLP/flair/)** (`pip install flair`)
```python
from flair.data import Sentence
from flair.models import SequenceTagger
# load tagger
tagger = SequenceTagger.load("{repo_id}")
# make example sentence
sentence = Sentence("Jean Paul Gaultier Classique - 50 ML Eau de Parfum Damen Parfum.")
# predict NER tags
tagger.predict(sentence)
# print sentence
print(sentence)
# print predicted NER spans
print('The following NER tags are found:')
# iterate over entities and print
for entity in sentence.get_spans('ner'):
print(entity)
```""" |