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telugu_bertu_ner
kuppuluri/telugu_bertu_ner
telugu_bertu_ner is a token classification model from kuppuluri. Use it when you need labels on individual words, such as names. It is set up for transformers.
Use the below script from your python terminal as the web interface for inference has few encoding issues for Telugu
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At a glance
- Task
- Token Classification
- Library
- transformers
- Model type
- bert
- Access
- Public
- Created
- Mar 2, 2022
- Updated
- Dec 2, 2021
- SHA
- c1649a30
Try a prompt
Model card
From the Hugging Face model README
Named Entity Recognition 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.
from simpletransformers.ner import NERModel
model = NERModel('bert',
'kuppuluri/telugu_bertu_ner',
labels=[
'B-PERSON', 'I-ORG', 'B-ORG', 'I-LOC', 'B-MISC',
'I-MISC', 'I-PERSON', 'B-LOC', 'O'
],
use_cuda=False,
args={"use_multiprocessing": 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 = 0.0004407190410447974
f1_score = 0.999519076627124
precision = 0.9994389677005691
recall = 0.9995991983967936
- Task
- Token Classification
- Library
- transformers
- Type
- bert
- Created
- Mar 2, 2022
- Updated
- Dec 2, 2021