Instructions to use ProbeX/Model-J__DINO__model_idx_0649 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_0649 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_0649") 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_0649") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0649", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5427334dda9b783904963c97a3bd5dffe1bb872dd4d15fc25e45b06d067210f8
- Size of remote file:
- 5.37 kB
- SHA256:
- 1d964757d0153f874ecbaaf69a1528ab00110700ee0f4fb445fb7c152036f8b2
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