Instructions to use Jeevesh8/bl__qqp_ft_3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/bl__qqp_ft_3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/bl__qqp_ft_3")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/bl__qqp_ft_3") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/bl__qqp_ft_3") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b234c8fb3717bd584268f5f37e33cbe76fb93111d8e577bfa77094a37ffd8a7f
- Size of remote file:
- 1.34 GB
- SHA256:
- 773e232280bfbbba76c7d4d6faba6b33e72b80a0e0232f6c3007e5cb28f577ac
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