Instructions to use Jeevesh8/bert_ft_qqp-99 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/bert_ft_qqp-99 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/bert_ft_qqp-99")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/bert_ft_qqp-99") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/bert_ft_qqp-99") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5fe0a8253561477b1c0efb78a90fadb290364edd956dac437cdd51aba301fea4
- Size of remote file:
- 438 MB
- SHA256:
- 4f83ffb8835562bc5ffeb21809d157abedca06edad9ed2a12f0df2f9351ca984
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