Instructions to use ProbeX/Model-J__DINO__model_idx_0435 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_0435 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_0435") 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_0435") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0435", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f3303c06d07f9aabe4ae2235d6750db23f69ec71584275bf78b77eb36190f7df
- Size of remote file:
- 343 MB
- SHA256:
- 535f2de285ab61e97289c239235ef2ae5e6404775a4295b25b572062d4bb2b15
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