Instructions to use ProbeX/Model-J__DINO__model_idx_0160 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_0160 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_0160") 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_0160") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0160", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2521b6cc89b1005185024e9c95fd34ca3bcdac2d2956cf81611751c094007c1a
- Size of remote file:
- 5.37 kB
- SHA256:
- d180aba986a86e7ae761943387c00c94f4835a5530090ed390fb3583a0db9a65
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