Instructions to use Jeevesh8/bt__qqp_ft_0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/bt__qqp_ft_0 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/bt__qqp_ft_0")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/bt__qqp_ft_0") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/bt__qqp_ft_0") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- be5657a0104348b986a314f2ac2da19cb0299a6ad2c4700ab95a38230609cfa9
- Size of remote file:
- 17.5 MB
- SHA256:
- 0e4d2a97b91ebc8db6f21f98cca2ddbca70143470035c5ef32a450966029c06d
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