Instructions to use ProbeX/Model-J__DINO__model_idx_0890 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_0890 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_0890") 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_0890") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0890", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 00a03994624c7f080493842530f3b074b910aa8f0661cda4ed9c19df0d1afe4e
- Size of remote file:
- 5.37 kB
- SHA256:
- 0592ec9f8073545eef4bbe6f208c3376047e42c7bb6be522c0996c2ea9ee5b1a
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