Instructions to use Jeevesh8/bl__qqp_ft_4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/bl__qqp_ft_4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/bl__qqp_ft_4")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/bl__qqp_ft_4") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/bl__qqp_ft_4") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 16b093efef2b59231941c1d8145801b0eef5f7cd522de87501302db6e77dce38
- Size of remote file:
- 1.34 GB
- SHA256:
- fc067188e0aca44a6ea12afc3177f838d653c8e17f164dae4ee8cfdafc83aa55
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