Instructions to use ProbeX/Model-J__SupViT__model_idx_0942 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_0942 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_0942") 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_0942") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0942", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e95a8ece4af3f75d9021337394afcd874928140a951166f31b27c8703a4adf77
- Size of remote file:
- 5.37 kB
- SHA256:
- 9d422ee8796a852484766098e069b81685ad655363677334f4ff118475540530
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