Instructions to use ProbeX/Model-J__DINO__model_idx_0347 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_0347 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_0347") 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_0347") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0347", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ce9dc41d3001a2011fc790735fe919b1b16d4967ecd81b66b80880bcfee92656
- Size of remote file:
- 5.37 kB
- SHA256:
- 9cb2c6b1723b5c8cbbe8c890150e9363159fea00cb0a1157c9deae74c3b2ee5c
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