Instructions to use Jeevesh8/bt__qqp_ft_11 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/bt__qqp_ft_11 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/bt__qqp_ft_11")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/bt__qqp_ft_11") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/bt__qqp_ft_11") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b7ffa283c9d7c9ee7a0603ad4c7ce66b54faa0bc2ea82d36700cb828e355364c
- Size of remote file:
- 17.5 MB
- SHA256:
- 582fdf0bf8e4e470f1131180e41aa297ff8f2bd81d57eb0d6371eb43e75a13b1
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