Instructions to use ProbeX/Model-J__SupViT__model_idx_0700 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_0700 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_0700", device_map="auto") 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_0700") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0700", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f297f25ce566f93561798ae3f53cc4f8d46060673ca075d23331ef13a2932bbe
- Size of remote file:
- 5.37 kB
- SHA256:
- 4309c087bff431421de8b14a8da540612f2d889a04ec7a8905433f7e5533858a
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