Instructions to use Jeevesh8/bert_ft_qqp-8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/bert_ft_qqp-8 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/bert_ft_qqp-8")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/bert_ft_qqp-8") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/bert_ft_qqp-8") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7c9f65ce75de7d0d59db9e8edf997a6784630bcdaaa4b3103ed7b608b378f2c0
- Size of remote file:
- 438 MB
- SHA256:
- ba250d0fdac77340016aa1d8aa4cdf4419f95feff4c2d70c96ef13f55a131968
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