Instructions to use ProbeX/Model-J__SupViT__model_idx_0355 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_0355 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_0355") 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_0355") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0355", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4fb52cf99540e39ccd5e6c532b15a5f2247fccd16ef3deb05091b18f6068b7a0
- Size of remote file:
- 5.37 kB
- SHA256:
- ffb23b5d7f260bdf60580460aed9e8266592a5cfdb4e16c3cfe7098810793039
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