Instructions to use Jeevesh8/bert_ft_qqp-53 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/bert_ft_qqp-53 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/bert_ft_qqp-53")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/bert_ft_qqp-53") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/bert_ft_qqp-53") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2964b6dd75662903436a6fa83413506f18eba6b07d91c2ce8d8df202e2cd9a15
- Size of remote file:
- 438 MB
- SHA256:
- d90ef2c6c071a22be729ab9fe8123c1c6122956e8308e4c1233e39215bc0ba5d
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