Instructions to use ProbeX/Model-J__SupViT__model_idx_0521 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_0521 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_0521") 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_0521") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0521", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9467597c77e30c9ce92cf80df11a33494144108d308e8bbc65c71643d3c80d9d
- Size of remote file:
- 5.37 kB
- SHA256:
- 9c62af283a7d77d0bf4b0eac49447852696c01ecbda776408c04ec0a939335d0
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