Instructions to use ProbeX/Model-J__DINO__model_idx_0949 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_0949 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_0949") 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_0949") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0949") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 62532be1fe5e7dbbb933d74e179314e756c28df053a8aef05121e863a25a9123
- Size of remote file:
- 5.37 kB
- SHA256:
- b39e53e7d1c407b271fcaca489f80e03f347838d5516da1d1b9714d62bcb0297
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