Instructions to use ProbeX/Model-J__SupViT__model_idx_0548 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_0548 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_0548") 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_0548") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0548", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d72c05a7644f6d90bc9798416bb90e937d318322f66e6cc319144419a3dd5a03
- Size of remote file:
- 5.37 kB
- SHA256:
- e9d7535b0a721651a7301cc5e457c9489158cccee42efd9be191aa4a23f46067
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