Instructions to use ProbeX/Model-J__DINO__model_idx_0885 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_0885 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_0885") 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_0885") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0885", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f6d5caf4dc2f7cf6bf54b60afdfe0d68d405726e8f37246ab123d7bf6d4465f0
- Size of remote file:
- 5.37 kB
- SHA256:
- e6fbdb378fbaf9fb4fbdc13b82dbddd170d8eb7b97a05f0c110d6deffb90feb4
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