Instructions to use ProbeX/Model-J__SupViT__model_idx_0229 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_0229 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_0229") 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_0229") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0229", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 76cb0e151ea02467d2907a5bb9ed2de0d0622b17789501a24a50ba15f178906a
- Size of remote file:
- 5.37 kB
- SHA256:
- 7c95e82dee662de5d7757dc8f9bb64e5e7d690c100992f8cbdb31f8027194cd2
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