Instructions to use ProbeX/Model-J__SupViT__model_idx_0903 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_0903 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_0903") 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_0903") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0903", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bfdd1a27e09eb7e6eec53c1b7eb5679a7493a47442407ca5cd35092d72bdd74c
- Size of remote file:
- 5.37 kB
- SHA256:
- 24aa903bab7557d9869fb6aaf92923fd4cd7f6ff5423ab2970934697f1174af5
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