Token Classification
Transformers
Safetensors
English
albert
ner
named-entity-recognition
indic-languages
bert
medical-nlp
regulatory
pharmaceutical
Instructions to use sharkdodo/Indic-Bert-NER-Model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sharkdodo/Indic-Bert-NER-Model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="sharkdodo/Indic-Bert-NER-Model")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("sharkdodo/Indic-Bert-NER-Model") model = AutoModelForTokenClassification.from_pretrained("sharkdodo/Indic-Bert-NER-Model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 98d09238c840741641fe6e2af82d29aa16057fa97bd1856a030db55096d46519
- Size of remote file:
- 5.43 kB
- SHA256:
- 830db2bf011be7a2281886b3573b9ffe271985c931a7ee03176a7e0f90c360c9
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