Instructions to use ProbeX/Model-J__DINO__model_idx_0386 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_0386 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_0386") 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_0386") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0386", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2b175c6d00b32bc21b682d6b52e11f4f4b488ab9eb30ebea233d18f96f119fea
- Size of remote file:
- 5.37 kB
- SHA256:
- f4b5e672a72b66c79de91a6b75b7f4ff0adb827f8a1db93ae06469eb5755ef28
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