Instructions to use Jeevesh8/bert_ft_qqp-48 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/bert_ft_qqp-48 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/bert_ft_qqp-48")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/bert_ft_qqp-48") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/bert_ft_qqp-48") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ff6d82317fc221070ebaf5a22e2c19c07977d24a36882d47f8a9ff606512a116
- Size of remote file:
- 438 MB
- SHA256:
- ac0ceff575ec1ae791f8e605629b91ead20fbf39f7111d09b941246cda49af27
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