Instructions to use Jeevesh8/bt__qqp_ft_15 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/bt__qqp_ft_15 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/bt__qqp_ft_15")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/bt__qqp_ft_15") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/bt__qqp_ft_15") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3fd75bbe62040b16ec66f0e8fd0eb3e7e604998ad01c0e03fe8c774697a82aa9
- Size of remote file:
- 17.5 MB
- SHA256:
- d5513f8a096e08233f5ce6f092088e574fc2e5ebcea88a08467615969a27d810
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