Instructions to use ProbeX/Model-J__DINO__model_idx_0185 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_0185 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_0185") 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_0185") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0185", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 83ecc8992dba65e80aa0161be667d65c6f44bc48cfefd1adfa3703c661e0fb98
- Size of remote file:
- 5.37 kB
- SHA256:
- 51da7b6b73d9a2b864f00c3b843cbcbce30d89561cb34d4fbcb609503ac6e11a
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