Instructions to use Digiquanta/Facesheet_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Digiquanta/Facesheet_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Digiquanta/Facesheet_classification")# Load model directly from transformers import AutoProcessor, AutoModelForSequenceClassification processor = AutoProcessor.from_pretrained("Digiquanta/Facesheet_classification") model = AutoModelForSequenceClassification.from_pretrained("Digiquanta/Facesheet_classification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 084fdac4b35b9b7bf813e15252880d5ebb7328a95c72f00e7ef1eb842af66bbf
- Size of remote file:
- 504 MB
- SHA256:
- f0cbdb6e9319cc7fa286f611eec237e5c8a68c5457ce8f57020bf54db32b1d55
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