Instructions to use ProbeX/Model-J__DINO__model_idx_0343 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_0343 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_0343") 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_0343") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0343", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 37c58c2423a6eb5997ea0cd86225bb328f027752d307b18da66ee1049a02a923
- Size of remote file:
- 5.37 kB
- SHA256:
- 4a065909afcf0230f3e6abbc83e185ddd5d69da5d44028ca374a7ca3dcb5d9e4
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