Instructions to use ProbeX/Model-J__SupViT__model_idx_0364 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_0364 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_0364") 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_0364") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0364", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b4b9a1306a3710a87ecb1c4148e8f77bdabea4cc6112fd7952913ce752b1e841
- Size of remote file:
- 5.37 kB
- SHA256:
- 4ee1e6edb1ea66b44d8a2ec60e2c9c015b569083c02b97cb93df47f8133695ef
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