Instructions to use Jeevesh8/bt__qqp_ft_18 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/bt__qqp_ft_18 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/bt__qqp_ft_18")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/bt__qqp_ft_18") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/bt__qqp_ft_18") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a91bd09b22fd222db491adb710bbebe19b5bb7dad8b33e3f5b3aa8f789cb1542
- Size of remote file:
- 17.5 MB
- SHA256:
- f26f89539a9b21f394da04edfd3839d6d3e90b2c89f862cc4d383e9dbaaca697
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