Instructions to use nzs234/siglip2-so400m-aesthetic-scorer-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nzs234/siglip2-so400m-aesthetic-scorer-v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="nzs234/siglip2-so400m-aesthetic-scorer-v1") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("nzs234/siglip2-so400m-aesthetic-scorer-v1", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5b45af73f6e0265033f468e10756bfe77c744af2b1f6628c611a15e888fafaee
- Size of remote file:
- 4.55 GB
- SHA256:
- a621bd212e1b3329b428595f9693217e19587afe826adf3e5c241a16392e8973
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