Instructions to use ProbeX/Model-J__DINO__model_idx_0004 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_0004 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_0004") 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_0004") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0004", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 655989beb9a87465ea6a6e0fc32fd915edb6b116450693eff3f352d8fdb6cbc1
- Size of remote file:
- 5.37 kB
- SHA256:
- f97c8d62c0c54ab3b8c475081969e868a93d04ee694fa2824a3971168b28341b
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