Instructions to use ProbeX/Model-J__DINO__model_idx_0071 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_0071 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_0071") 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_0071") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0071", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e5a88bb8eba904b3d343b64c7e72922e8f7841591db93e8507f51082430cc12f
- Size of remote file:
- 5.37 kB
- SHA256:
- 874869628261b37ba96660772f71d8e186f1fb848ff0ff553bd3ac96228cca9d
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