Instructions to use ProbeX/Model-J__SupViT__model_idx_0609 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_0609 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_0609") 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_0609") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0609", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f0232bd505b15e0bad847fdd03605b26e9c413c52e044581bae3b7920e0ad024
- Size of remote file:
- 5.37 kB
- SHA256:
- e14320f1a543f04de7e38085027310ebdcc40ccfd43d5cbab60e64892b024505
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