Instructions to use Jeevesh8/bl__qqp_ft_1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/bl__qqp_ft_1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/bl__qqp_ft_1")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/bl__qqp_ft_1") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/bl__qqp_ft_1") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 74e2776b0df5b94d45845de833cdd53ba66cdc1a49a84cb488cd9210b1703d92
- Size of remote file:
- 1.34 GB
- SHA256:
- 378c966df8c7d8e225269b1548fa0cf9c21b8e556007658e42b649804109f655
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