Instructions to use ProbeX/Model-J__DINO__model_idx_0014 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_0014 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_0014") 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_0014") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0014", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8c007bb9bac3a883305cf343e93525ba3e3c98b3e5fde34a69c3aa9aaba28f87
- Size of remote file:
- 5.37 kB
- SHA256:
- 816d9d8b4980384ccdd87b48b5842b481a77a4adb694430ae1299c4153dd4b01
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