Instructions to use gowitheflow/p9-iter3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gowitheflow/p9-iter3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="gowitheflow/p9-iter3")# Load model directly from transformers import AutoModelForSequenceClassification model = AutoModelForSequenceClassification.from_pretrained("gowitheflow/p9-iter3", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 71f8f1b194ce3d22d09267a821d84ede0b30f5027a91c6d5a7bd33192e12e36b
- Size of remote file:
- 690 MB
- SHA256:
- e90b244bf52ef6c60b7507458d77609c1d26b529bbd9311c7668743b60cb3dde
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