Instructions to use ProbeX/Model-J__SupViT__model_idx_0691 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_0691 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_0691") 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_0691") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0691") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0dceebccef0e8dae7131979fe43b5018d5de4f9b70d360a9e6cb5a5c991aff22
- Size of remote file:
- 5.37 kB
- SHA256:
- 4534964b8b87e48f18cf5752531771902bfba2f74e644bd9cd13d7a5fb0195e7
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