Instructions to use ProbeX/Model-J__DINO__model_idx_0575 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ProbeX/Model-J__DINO__model_idx_0575 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="ProbeX/Model-J__DINO__model_idx_0575") 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__DINO__model_idx_0575") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0575", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3c7fe07ab84283b38620914a7db3baa3e31f4dafa4a9ad229feb961eb582e7c8
- Size of remote file:
- 5.37 kB
- SHA256:
- 960ab158c995dfa99bd916511d9e47a7159c63ddfa3a703cf23f1b5f2fba85a4
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