Instructions to use ProbeX/Model-J__DINO__model_idx_0970 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_0970 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_0970") 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_0970") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0970", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 780593f03e4ba0f28d528cfe3499e2e4fa75e1b0eac604dc3ae6508f93473dce
- Size of remote file:
- 5.37 kB
- SHA256:
- f52c6e9b431e3fa9ea0b2f43f00b1fbbd4d6caed31613ab4eb9a8f2fb1b549e6
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