Instructions to use ProbeX/Model-J__DINO__model_idx_0248 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_0248 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_0248") 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_0248") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0248") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f72fdab38fa56c335fd160bcb2d36e6ebe40bacd70500e1f579101f1df7f7437
- Size of remote file:
- 5.37 kB
- SHA256:
- 486979b10061b5e25bf579523f0483298a57bbb6956cd921efe47dfca34ff0e0
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