Instructions to use ProbeX/Model-J__DINO__model_idx_0023 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_0023 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_0023") 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_0023") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0023", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0c8892f970f4ab57598c761cb7c3215eb75c684a4cd8f94d52a5feed6b138071
- Size of remote file:
- 5.37 kB
- SHA256:
- 6e181fd685916a9f8eb4a0481cb9aff98db6bdd476a09bd6a6b1acf79e29cc9f
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