Instructions to use prithivMLmods/Fashion-Mnist-SigLIP2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use prithivMLmods/Fashion-Mnist-SigLIP2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="prithivMLmods/Fashion-Mnist-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/Fashion-Mnist-SigLIP2") model = AutoModelForImageClassification.from_pretrained("prithivMLmods/Fashion-Mnist-SigLIP2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3251de6e6b66387dc552d1cf7d0793718eea2e2f86e83eead3396b6e21a41794
- Size of remote file:
- 372 MB
- SHA256:
- de996bc92de10f2d1ef53b6678ea57f3c3ebcd31fb3d485729c6bb067e1af6bb
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