Instructions to use Jeevesh8/bl__qqp_ft_0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/bl__qqp_ft_0 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/bl__qqp_ft_0")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/bl__qqp_ft_0") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/bl__qqp_ft_0") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7ff97b0ef7675f755a7847c38e3d8ab185a9fdcc491b3447e4f35ec2b0bee163
- Size of remote file:
- 1.34 GB
- SHA256:
- 37c3e76df738ba24a1e84a80bb907bee46581d7697a60e0fde7ed15ef6f8b38d
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