Instructions to use ProbeX/Model-J__SupViT__model_idx_0826 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_0826 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_0826") 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_0826") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0826", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- dcdb35a252971dcaa9b01d5df10d029eea7632f0dedad0f59abae3a5412b5d32
- Size of remote file:
- 5.37 kB
- SHA256:
- e2458525ab9da6a82488ce603f99da4df49004b442da9c4518f28fc6791d1e93
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