Instructions to use ProbeX/Model-J__DINO__model_idx_0072 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_0072 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_0072") 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_0072") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0072", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6587dc30e1b41388640c0985c9c1052a3caacd8fb14038da3c7f34039bf8290c
- Size of remote file:
- 343 MB
- SHA256:
- f5b333abb2e9ead0cb21a395a54758108230dafc0c207e915ee51deaa29947e5
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