Instructions to use Jeevesh8/bert_ft_qqp-41 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/bert_ft_qqp-41 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/bert_ft_qqp-41")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/bert_ft_qqp-41") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/bert_ft_qqp-41") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cb240162ba1e2ab11802520159f0d6b09991600711760043e7146dad95e5f568
- Size of remote file:
- 438 MB
- SHA256:
- a51e088ae1df160fa54e49b8668b1b7af20aba4b65b5f585df16a81a7a86319c
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