Instructions to use ProbeX/Model-J__DINO__model_idx_0832 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_0832 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_0832") 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_0832") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0832", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5ad1352fc692d08698690c0debdbf9775317f9b154c7cbc2e480ce9b3c776422
- Size of remote file:
- 5.37 kB
- SHA256:
- 1863f648c00ca25d7e24b6692b9ccca14421226d94a1c42dc2adf859d8300d13
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