Instructions to use ProbeX/Model-J__DINO__model_idx_0510 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_0510 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_0510") 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_0510") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0510", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7c229d36d094d46721bb96fbc989331fa4f72e0b2d86e169912eaa62a3dc1b8a
- Size of remote file:
- 5.37 kB
- SHA256:
- d28a57cdc8e5e61a0c66437375a988b89b92bf35bf1b514685556ddf98b7bf38
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