Instructions to use ProbeX/Model-J__DINO__model_idx_0950 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_0950 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_0950") 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_0950") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0950", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 385066bc501790bf397245e792ae43ddf783dc251dcd1ad56200e79814d90c0d
- Size of remote file:
- 5.37 kB
- SHA256:
- 0f2601380571b14979103ae50bcc29746f234b6f965883c39e622dc5d2e5f8cb
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