Instructions to use neuropark/sahajBERT-NER with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use neuropark/sahajBERT-NER with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="neuropark/sahajBERT-NER")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("neuropark/sahajBERT-NER") model = AutoModelForTokenClassification.from_pretrained("neuropark/sahajBERT-NER", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7ba2695734184b7a6d1def9bacb84d05b24f1042beded719f70112bfd3c46c53
- Size of remote file:
- 67.6 MB
- SHA256:
- 7821a60cc677b98933f476601c85039ce3b188cc179238c4de289d52d194b6eb
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