Instructions to use ProbeX/Model-J__SupViT__model_idx_0055 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_0055 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_0055") 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_0055") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0055", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 28181790a77748208b384e1ee52b1f806919f24e2d861b80c6391843c4730c69
- Size of remote file:
- 5.37 kB
- SHA256:
- 4719a6f6c9f05cab2da7b4bb66de271ade8d6cc7b4dcd4e3c9c750b1e33becc8
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