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# Part of Speech tagging Model for Telugu
#### How to use
Use the below script from your python terminal as the web interface for inference has few encoding issues for Telugu
PS: If you find my model useful, I would appreciate a note from you as it would encourage me to continue improving it and also add new models.
```python
from simpletransformers.ner import NERModel
model = NERModel('bert',
'kuppuluri/telugu_bertu_pos',
args={"use_multiprocessing": False},
labels=[
'QC', 'JJ', 'NN', 'QF', 'RDP', 'O',
'NNO', 'PRP', 'RP', 'VM', 'WQ',
'PSP', 'UT', 'CC', 'INTF', 'SYMP',
'NNP', 'INJ', 'SYM', 'CL', 'QO',
'DEM', 'RB', 'NST', ],
use_cuda=False)
text = "విరాట్ కోహ్లీ కూడా అదే నిర్లక్ష్యాన్ని ప్రదర్శించి కేవలం ఒక పరుగుకే రనౌటై పెవిలియన్ చేరాడు ."
results = model.predict([text])
```
## Training data
Training data is from https://github.com/anikethjr/NER_Telugu
## Eval results
On the test set my results were
eval_loss = 0.0036797842364565416
f1_score = 0.9983795127912227
precision = 0.9984325602401637
recall = 0.9983264709788816
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