Instructions to use ProbeX/Model-J__DINO__model_idx_0715 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_0715 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_0715") 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_0715") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0715", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b78506ccf31f9c502e25c61b86d9676a2a21b7dc474d48b938f8bf3396dd6f1b
- Size of remote file:
- 5.37 kB
- SHA256:
- 26940932878f25baf545146a2ae527dd6c4600001de18898cef2d9437a179903
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