Instructions to use ProbeX/Model-J__DINO__model_idx_0345 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_0345 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_0345") 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_0345") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0345", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 249031d9a4549bd93daf28b54083ceee8d25a1ce11c5bc4f88200c7e1fe1fb9c
- Size of remote file:
- 343 MB
- SHA256:
- 834b7f5352f9f695e7b58662792b19b8791c112ba3797a98f137fc98574c1928
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