Instructions to use Jeevesh8/init_bert_ft_qqp-51 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/init_bert_ft_qqp-51 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/init_bert_ft_qqp-51")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/init_bert_ft_qqp-51") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/init_bert_ft_qqp-51") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b3f061ffeca77699c67305dca5232540b5143b27a3474f22fd57f2a59c27c1d6
- Size of remote file:
- 438 MB
- SHA256:
- 7ba28396255880a742366fadf448902392ee92113fcdc4bf646d742cee32e8f8
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