Instructions to use ProbeX/Model-J__SupViT__model_idx_0763 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_0763 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_0763") 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_0763") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0763", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 00bfadc51d07e016902c76bd1243e9cc52cbad0ce1bd74baf16cf2f38ddac5a1
- Size of remote file:
- 5.37 kB
- SHA256:
- ffa96382af497ff57ead0239f1b6c6a9ccbc96ee4833eb70c5a3cccba53c2205
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