Instructions to use Jeevesh8/bt__qqp_ft_4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/bt__qqp_ft_4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/bt__qqp_ft_4")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/bt__qqp_ft_4") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/bt__qqp_ft_4") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fe814feac6f4bd039863a7ec1df8683cb38759f6d95f2e9afad6d060cee69364
- Size of remote file:
- 17.5 MB
- SHA256:
- 33e0f362be2a6c25b5b6f0302634a552c15790f8e48055e7081f140d51288760
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