Instructions to use prithivMLmods/Multilabel-Portrait-SigLIP2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use prithivMLmods/Multilabel-Portrait-SigLIP2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="prithivMLmods/Multilabel-Portrait-SigLIP2") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoProcessor, AutoModelForImageClassification processor = AutoProcessor.from_pretrained("prithivMLmods/Multilabel-Portrait-SigLIP2") model = AutoModelForImageClassification.from_pretrained("prithivMLmods/Multilabel-Portrait-SigLIP2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 72c75f3f8604b5497b3071e9d47353f98ceecffffb029368b45717add376558f
- Size of remote file:
- 687 MB
- SHA256:
- d0d34855df5fd43a18cf6b12e503a0eb445813038330fae709e5c09ce3ab27d4
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