Instructions to use ProbeX/Model-J__DINO__model_idx_0092 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_0092 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_0092") 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_0092") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0092", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6defe84c88f92441159504f7c291f28d745089f0a6bdfaae34b34cbe9f584533
- Size of remote file:
- 5.37 kB
- SHA256:
- 2a705e6c7fd8da19617da9ab0672a3cb8371df6a437b4b866a88cfe411f738fe
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