Instructions to use ProbeX/Model-J__SupViT__model_idx_0830 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_0830 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_0830") 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_0830") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0830", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f6ba58f645d525149b4b1e3c7b86d4e3f61314a82ef449719d83dd1a9ee6263a
- Size of remote file:
- 5.37 kB
- SHA256:
- bae81a32ce452c82f680f5999a0bc065ec3ce8601d112bc62cdc4c718ec4038d
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