Instructions to use ProbeX/Model-J__DINO__model_idx_0446 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_0446 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_0446") 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_0446") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0446") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d8c58d3806ec812580f419851c0cb59f5ddb1810e9a5aaa41bc0cadda5763443
- Size of remote file:
- 5.37 kB
- SHA256:
- d7728ec3681f93e50904efc117553ac003e11c95680862f74879437ab8bbb5bc
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