Instructions to use Jeevesh8/bert_ft_qqp-76 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/bert_ft_qqp-76 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/bert_ft_qqp-76")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/bert_ft_qqp-76") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/bert_ft_qqp-76") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a938820a4132f974f7d9c6579f434b266608bb6ff71b26cd7aa6ee80f535e53f
- Size of remote file:
- 438 MB
- SHA256:
- c05423c1d5f5caecb69a74fb22d20d21e583641715513a722f2f89f9b589b4f5
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