Instructions to use ProbeX/Model-J__DINO__model_idx_0596 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_0596 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_0596") 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_0596") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0596", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 25098daeec04db3635ebd6c9b30c5bd819a95ba67ce2443d9ce5c6e6d772e5eb
- Size of remote file:
- 343 MB
- SHA256:
- 877cc42a4cbc51d54b1c2ae90c297ca9dc1fa10a37d806668d02e74b0d7b8690
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