Instructions to use Abhi964/MahaPhrase_IndicBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Abhi964/MahaPhrase_IndicBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Abhi964/MahaPhrase_IndicBERT")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Abhi964/MahaPhrase_IndicBERT") model = AutoModelForSequenceClassification.from_pretrained("Abhi964/MahaPhrase_IndicBERT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cd31b8be9d2e721fa2a0cb4e0dd3f0781ac2280666250ffb786fceccf07936f4
- Size of remote file:
- 15.3 MB
- SHA256:
- 94d9a76949689d0d9561ff6a24171d0bc10423b5964183e9d59ac5a08f598964
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