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--- |
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language: |
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- es |
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license: isc |
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library_name: flair |
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tags: |
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- flair |
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- token-classification |
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metrics: |
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- f1 |
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- precision |
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- recall |
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- accuracy |
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widget: |
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- text: "Jean Paul Gaultier Classique - 50 ML Eau de Parfum Damen Parfum" |
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--- |
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### Demo: How to use in Flair |
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Requires: |
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- **[Flair](https://github.com/flairNLP/flair/)** (`pip install flair`) |
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```python |
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from flair.data import Sentence |
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from flair.models import SequenceTagger |
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# load tagger |
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tagger = SequenceTagger.load("lighthousefeed/yoda-ner") |
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# make example sentence |
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sentence = Sentence("Jean Paul Gaultier Classique - 50 ML Eau de Parfum Damen Parfum.") |
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# predict NER tags |
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tagger.predict(sentence) |
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# print sentence |
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print(sentence) |
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# print predicted NER spans |
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print('The following NER tags are found:') |
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# iterate over entities and print |
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for entity in sentence.get_spans('ner'): |
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print(entity) |
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``` |
