Instructions to use Jeevesh8/bert_ft_qqp-4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/bert_ft_qqp-4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/bert_ft_qqp-4")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/bert_ft_qqp-4") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/bert_ft_qqp-4") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8d71bf6ce517bf34641034d5549ca0c750f13c5119247e3c5527754df8caf071
- Size of remote file:
- 438 MB
- SHA256:
- fce238cca280b983a825be8442cf66c7b891da441a624c6d135622270ca0c7da
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