Instructions to use ProbeX/Model-J__DINO__model_idx_0224 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_0224 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_0224") 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_0224") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0224", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bb37741484a1523c6b5c885a34cc90bdc5a1877e98fd131582cb1eafc9e761b7
- Size of remote file:
- 5.37 kB
- SHA256:
- e02a7b7fe76b8c1984b88e3d02faf9fd4eee9c922183b3d6f3c52c1162e40a77
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