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:
- 805209d6a20a00f4a8a4ff7b41e87f23c03fa581aac5ffb655b6baad114a6a40
- Size of remote file:
- 15.3 MB
- SHA256:
- 24d492b53d7397373ecb2b56998429fbadec938c74ff26582202bbc1cac23bc5
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