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:
- 75441a61d8d58186326ceee7e443a20a0edb831732ab17d66430fe58a60d473e
- Size of remote file:
- 687 MB
- SHA256:
- 1c75f03d71130e291a52f57b11c5ddc33e0fafeea0a7a621e1e4f19fc820b827
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