|
--- |
|
tags: |
|
- flair |
|
- token-classification |
|
- sequence-tagger-model |
|
language: en |
|
datasets: |
|
- conll2003 |
|
inference: false |
|
--- |
|
|
|
## Flair NER model `en-ner-conll03-v0.4.pt` |
|
|
|
Imported from https://nlp.informatik.hu-berlin.de/resources/models/ner/ |
|
|
|
### Demo: How to use in Flair |
|
|
|
```python |
|
from flair.data import Sentence |
|
from flair.models import SequenceTagger |
|
|
|
sentence = Sentence( |
|
"My name is Julien, I currently live in Paris, I work at Hugging Face, Inc." |
|
) |
|
|
|
tagger = SequenceTagger.load("julien-c/flair-ner") |
|
|
|
|
|
# predict NER tags |
|
tagger.predict(sentence) |
|
|
|
# print sentence with predicted tags |
|
print(sentence.to_tagged_string()) |
|
|
|
|
|
``` |
|
|
|
yields the following output: |
|
|
|
> `My name is Julien <S-PER> , I currently live in Paris <S-LOC> , I work at Hugging <B-LOC> Face <E-LOC> .` |
|
|
|
|
|
### Thanks [@stefan-it](https://huggingface.co/stefan-it) for the Flair integration ❤️ 🔥 |
|
|
|
|
