Instructions to use Jeevesh8/bt__qqp_ft_21 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/bt__qqp_ft_21 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/bt__qqp_ft_21")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/bt__qqp_ft_21") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/bt__qqp_ft_21") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6e4382c03713ee7e572193c751aa08204c4195472d0f1f14159d9ff20a17d6b6
- Size of remote file:
- 17.5 MB
- SHA256:
- fd09ed6ffe2b6b76e3924f5041afd801db9e0616ecfd12554141f2c072d5b5a4
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