Instructions to use ProbeX/Model-J__SupViT__model_idx_0296 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_0296 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_0296") 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_0296") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0296", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e68c8cf641ef0c95fc980e55636c4ac9701583b18c19252e252bf2f779052323
- Size of remote file:
- 5.37 kB
- SHA256:
- 6bd1b70c0335fca746bd8c3758d8c6f8cd796546aa884ff4f9c285abf035b1de
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