Instructions to use Jeevesh8/bert_ft_qqp-71 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/bert_ft_qqp-71 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/bert_ft_qqp-71")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/bert_ft_qqp-71") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/bert_ft_qqp-71") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 570a52c91cfedcddfeb3e1397d66fa24307ac4a4facf4deb1d19ab1072fae329
- Size of remote file:
- 438 MB
- SHA256:
- 9a1f8a5a384ec4c82437f2a5ffc221fc637d4713cd64edb48090038ccec08c58
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