Instructions to use Suramya/Best_Model_indic_bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Suramya/Best_Model_indic_bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Suramya/Best_Model_indic_bert")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Suramya/Best_Model_indic_bert") model = AutoModelForSequenceClassification.from_pretrained("Suramya/Best_Model_indic_bert") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cfc05ff7aac9a4a71c95744f4f146ca01b66966d24db6bafd6e4a8eff97f42d2
- Size of remote file:
- 15.3 MB
- SHA256:
- 929f9b0210a7a7bda5ed970c923ae3721cba6e8ae0a8548824392bea2bd4fe26
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