Instructions to use callmesan/indic-bert-hinglish-binary with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use callmesan/indic-bert-hinglish-binary with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="callmesan/indic-bert-hinglish-binary")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("callmesan/indic-bert-hinglish-binary") model = AutoModelForSequenceClassification.from_pretrained("callmesan/indic-bert-hinglish-binary") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 822caaab6f7cfd37a1bab26158d68fd9ec4adc2b3065cf873be39d67ad198525
- Size of remote file:
- 134 MB
- SHA256:
- 5447a03cfd6ee5aeb4963ed0917c1f0642cac5a318e9fe97c3646ddca52aeac5
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