Instructions to use sumitrsch/Indic-bert_multiconer22_bn with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sumitrsch/Indic-bert_multiconer22_bn with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="sumitrsch/Indic-bert_multiconer22_bn")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("sumitrsch/Indic-bert_multiconer22_bn") model = AutoModelForTokenClassification.from_pretrained("sumitrsch/Indic-bert_multiconer22_bn") - Notebooks
- Google Colab
- Kaggle
# Load model directly
from transformers import AutoTokenizer, AutoModelForTokenClassification
tokenizer = AutoTokenizer.from_pretrained("sumitrsch/Indic-bert_multiconer22_bn")
model = AutoModelForTokenClassification.from_pretrained("sumitrsch/Indic-bert_multiconer22_bn")Quick Links
Put this model path in variable best_model_path in first cell of given colab notebook for testing semeval multiconer task for bangla track. https://colab.research.google.com/drive/1P9827acdS7i6eZTi4B0cOms5qLREqvUO
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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="sumitrsch/Indic-bert_multiconer22_bn")