Instructions to use ProbeX/Model-J__DINO__model_idx_0336 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_0336 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_0336") 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_0336") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0336", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e4acffdeb8eaf3779cd826c26f9f13bcd31ed38f0aea3e39e366ca7f3762d518
- Size of remote file:
- 5.37 kB
- SHA256:
- 249394b02d3fb07db387830aaf1df53402469285674aa8a7c9f2111e74efe205
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