Instructions to use ProbeX/Model-J__SupViT__model_idx_0852 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ProbeX/Model-J__SupViT__model_idx_0852 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="ProbeX/Model-J__SupViT__model_idx_0852") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0852") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0852", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d18c541f60514529de069c7cdf964d3dc16471d391cd12df6cf39c09e71d4024
- Size of remote file:
- 5.37 kB
- SHA256:
- 19d6085dc7e562618786fec19fecf1aa2a7c3b5c52a8ce12ea23be3adf8b3282
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