tags: | |
- flair | |
- token-classification | |
- sequence-tagger-model | |
### Demo: How to use in Flair | |
Requires: | |
- **[Flair](https://github.com/flairNLP/flair/)>=0.14.0** (`pip install flair` or `pip install git+https://github.com/flairNLP/flair.git`) | |
```python | |
from flair.data import Sentence | |
from flair.nn import Classifier | |
from flair.tokenization import SciSpacyTokenizer | |
# load tagger | |
tagger = Classifier.load("regel-corpus/hunflair2-regel-tissue") | |
# make example sentence | |
sentence = Sentence("TNF-like factor that is both produced by osteoblasts, mesenchymal cells, " | |
"and activated T cells and required for osteoclast maturation and survival." | |
use_tokenizer=SciSpacyTokenizer()) | |
# 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) | |
``` | |