Instructions to use ProbeX/Model-J__SupViT__model_idx_0021 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_0021 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_0021") 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_0021") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0021", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 192515611076130a726d1804f4e02eac03ee682eaaac8c5e8869a77dc2114edc
- Size of remote file:
- 343 MB
- SHA256:
- 3955a9483f151fcdd71e04bd52b173cd21c6ec769106b13fbb54109577fd4b4d
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