Instructions to use Jeevesh8/bs__qqp_ft_3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/bs__qqp_ft_3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/bs__qqp_ft_3")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/bs__qqp_ft_3") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/bs__qqp_ft_3") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 08b4e27d82394dd04e8b0bf91632eb378334c91822470da6ff43f753a45aeb47
- Size of remote file:
- 115 MB
- SHA256:
- ecd74b9171eb5fa77fba145cf77f168ff9d2544c2ab1809044b7eb19c750fe07
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