Instructions to use defefekt/PDLO_Classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use defefekt/PDLO_Classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="defefekt/PDLO_Classifier") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("defefekt/PDLO_Classifier") model = AutoModelForImageClassification.from_pretrained("defefekt/PDLO_Classifier") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a63a0d3b83659f125b96cb90b7cbe2b2cabda41be0f862c16b8d6ed4b05888b4
- Size of remote file:
- 781 MB
- SHA256:
- 9edd84bb8d05044392bd402b8c1b4ea2c5bd82ef5c446cce46db4fcb63e1a615
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