Instructions to use ProbeX/Model-J__DINO__model_idx_0967 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_0967 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_0967") 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_0967") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0967", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 19c61e3eb30d4aa8243ff813101e87daddb48e078317c33476c8c6d2cc2a92b6
- Size of remote file:
- 5.37 kB
- SHA256:
- 54b2be2845687eafcde73efa5f89d2a37f9edf1718319e2ebd90fa810d8ce2a2
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