Instructions to use ProbeX/Model-J__SupViT__model_idx_0996 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_0996 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_0996") 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_0996") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0996", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6bc54af9cd5e24ff26f828d8a14bf3a28febab196ee9fd52cd2c9e2c781b3470
- Size of remote file:
- 5.37 kB
- SHA256:
- 24244f335a55e8a6ce2b5e78e0ee73d07d24f667fc531fef63f97ec017d5775c
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