Instructions to use ProbeX/Model-J__SupViT__model_idx_0121 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_0121 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_0121") 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_0121") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0121", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ccd9b5ed4f2a50e6c23e1bb00015194fcafdf2857ba385a273d8ac3323c71f20
- Size of remote file:
- 5.37 kB
- SHA256:
- 6b06ec29019c5e06d5b80e98ebc3f6f5eb80260e5285ec30d28c86f065b2d9ac
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