Instructions to use l3cube-pune/marathi-ner-iob with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use l3cube-pune/marathi-ner-iob with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="l3cube-pune/marathi-ner-iob")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("l3cube-pune/marathi-ner-iob") model = AutoModelForTokenClassification.from_pretrained("l3cube-pune/marathi-ner-iob") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0c440cbbd9b52943c71f29962b69e31692b27b16f4c938f13d85a950152a1d5a
- Size of remote file:
- 709 MB
- SHA256:
- e4376b590ebc948fec77e0c323f0d6491899d97aaf1d36cc7df8f5db17dd0e04
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