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:
- 4ff2897bd5059fe48108ea9032ae521e1e3b7307cc4bb717cbcc89da26f86e90
- Size of remote file:
- 14.4 MB
- SHA256:
- ce5df2a40a4d30116f225cc56bdbf07c82efe1fadbcf41ba26d589513afce139
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