Instructions to use ProbeX/Model-J__SupViT__model_idx_0949 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_0949 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_0949") 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_0949") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0949") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- aa9440606f93f110059e4187d1b4539fb996a949c25f914120872c0dacc0593b
- Size of remote file:
- 5.37 kB
- SHA256:
- bec09763adbb08fd8f5295c0f21fb49388a095a974e79af344d6efbf447c06b2
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