Instructions to use ProbeX/Model-J__DINO__model_idx_0710 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_0710 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_0710") 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_0710") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0710", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5bd63550ee594a0434b47c3c38f404e43e6e7dbbab72b11ed44a860e82c66580
- Size of remote file:
- 343 MB
- SHA256:
- f301da6815b59db64ab9f84bd823a736d5116d2d6e179dc33947ec92973b9c6c
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