Instructions to use ProbeX/Model-J__SupViT__model_idx_0686 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_0686 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_0686") 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_0686") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0686") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a421dd2c984d055a229fc87b5abf9e2918c9e4b2e9fad600a75e19b787e67703
- Size of remote file:
- 5.37 kB
- SHA256:
- 18134785f89f03a00e0d23c35392f969bef87b5271597cde615d42af102d12fb
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