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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 567a18e72d903678ea6ad3ace6b3f6433483c208908d8ff7599e0705cfef9d46
- Size of remote file:
- 372 MB
- SHA256:
- d1364f1642175cfd4f7679aabac20bc65eb55ffdaa31ff2c441c9f668d7a9de1
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