Instructions to use ProbeX/Model-J__SupViT__model_idx_0788 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_0788 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_0788", device_map="auto") 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_0788") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0788", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3d0d04ff00b2fa663b452ac4b0d45152b4884e08d55e76c721d34acf3f1e12c8
- Size of remote file:
- 5.37 kB
- SHA256:
- 0395c74065919860986af241abe9e7ca2a82cae895cc4a39e718f11dc159487c
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