Instructions to use Jeevesh8/bert_ft_qqp-73 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/bert_ft_qqp-73 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/bert_ft_qqp-73")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/bert_ft_qqp-73") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/bert_ft_qqp-73") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d24c0888496bd00ecf7b043a8741bf35317b9bcb1740986de428d90eb1d0a9cc
- Size of remote file:
- 438 MB
- SHA256:
- a632b931f82bce6c9bb873917f26d7a509c30688fc7a83979137ae391a4628c9
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