Instructions to use Jeevesh8/bert_ft_qqp-13 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/bert_ft_qqp-13 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/bert_ft_qqp-13")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/bert_ft_qqp-13") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/bert_ft_qqp-13") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b8054da8ba163854e7e166da4f66ce17e1740199b565b6c83ade6fb781a590a6
- Size of remote file:
- 438 MB
- SHA256:
- bb6a73c72c9e79eb965cc5efc6a0f45b6c65276668266f5877b30c4c87daed4b
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