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:
- 869abb0c256be5b2a6e660d4180acb3abf8c077b51a3912ffb995012b9335c19
- Size of remote file:
- 134 MB
- SHA256:
- 898b6b5196159ed679860a0ad5cb2ead2ba31e3fe377f94c72d08a545a91a0ee
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