Instructions to use ProbeX/Model-J__DINO__model_idx_0926 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_0926 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_0926") 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_0926") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0926", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 727920e3492b39481f0375f2132d85e75fb37cd7bfaa2dd249d19a7dbaa4fdfd
- Size of remote file:
- 343 MB
- SHA256:
- 1a37c5412ab377fe061804d55bfac04c1222cbe4493d2a85536588fe1b33ff0a
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