Instructions to use ProbeX/Model-J__DINO__model_idx_0021 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_0021 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_0021") 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_0021") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0021", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4e34aeab9575290e15bfff33417e8a1f91f2ed37cd2a815bac1a425c9348e5fd
- Size of remote file:
- 5.37 kB
- SHA256:
- 7a620cbedda2e57cf5a5baeb95accfb3861b953d8be7fd86d42579200554522d
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