Instructions to use ProbeX/Model-J__DINO__model_idx_0224 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_0224 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_0224") 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_0224") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0224", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d1d88b7700155acc80c5453dc323ca074ebbe7b83ba9c37d358687f3adc31358
- Size of remote file:
- 343 MB
- SHA256:
- 91b62e575b4372e326161809967be23af49ef13334d15a17a09741b5dc2a371b
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