Instructions to use ProbeX/Model-J__SupViT__model_idx_0068 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_0068 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_0068") 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_0068") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0068", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2177c47796a49fa0220c435ca2032bd0b4b6195eab786e55c362468c48378a09
- Size of remote file:
- 5.37 kB
- SHA256:
- 8f2ebc71c255d1d8b6bafe9b6573bb5afaa4b5f86fcad45041943088f1137706
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