Instructions to use pickapic-anonymous/PickScore_v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pickapic-anonymous/PickScore_v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-image-classification", model="pickapic-anonymous/PickScore_v1") pipe( "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png", candidate_labels=["animals", "humans", "landscape"], )# Load model directly from transformers import AutoProcessor, AutoModelForZeroShotImageClassification processor = AutoProcessor.from_pretrained("pickapic-anonymous/PickScore_v1") model = AutoModelForZeroShotImageClassification.from_pretrained("pickapic-anonymous/PickScore_v1") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 66eb1668c574898f5608440ff9e93875bfaa9f94aaf019ed2fb3e7d61f136465
- Size of remote file:
- 3.94 GB
- SHA256:
- 3f0cf1c6e533f478534404cb3ca6938103becbfe4312c6affc077c274a757972
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