Instructions to use Jeevesh8/bt__qqp_ft_14 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/bt__qqp_ft_14 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/bt__qqp_ft_14")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/bt__qqp_ft_14") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/bt__qqp_ft_14") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 47e0413ffa52b8ab7dacd969cb9520507b112699d821d6523cbaedad54444dc8
- Size of remote file:
- 17.5 MB
- SHA256:
- fd68e51ee10c46d1bc0fa405fa3f8e5cd9d948c126cc9fd7cc02530c0d56a983
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