
# Flair NER fine-tuned on Private Dataset

This is specifically Designed on locations. the tag is <unk>

```python
from flair.data import Sentence
from flair.models import SequenceTagger
# load tagger
tagger = SequenceTagger.load("Saisam/Inquirer_ner_loc")
# make example sentence
sentence = Sentence("George Washington went to Washington")
# 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)
```


```
@inproceedings{akbik2018coling,
  title={Contextual String Embeddings for Sequence Labeling},
  author={Akbik, Alan and Blythe, Duncan and Vollgraf, Roland},
  booktitle = {{COLING} 2018, 27th International Conference on Computational Linguistics},
  pages     = {1638--1649},
  year      = {2018}
}
```
{"language": "en", "tags": ["flair"], "datasets": ["conll2003"]}
flair pytorch en dataset:conll2003 region:us
TAGS
#flair #pytorch #en #dataset-conll2003 #region-us 


# Flair NER fine-tuned on Private Dataset

This is specifically Designed on locations. the tag is <unk>





# Flair NER fine-tuned on Private Dataset

This is specifically Designed on locations. the tag is <unk>
TAGS
#flair #pytorch #en #dataset-conll2003 #region-us 
 # Flair NER fine-tuned on Private Dataset

This is specifically Designed on locations. the tag is <unk>
passage: TAGS
#flair #pytorch #en #dataset-conll2003 #region-us 
# Flair NER fine-tuned on Private Dataset

This is specifically Designed on locations. the tag is <unk>