Instructions to use ProbeX/Model-J__DINO__model_idx_0385 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_0385 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_0385") 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_0385") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0385", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d51cb0ce67b1f63c11c3fe0e7276157ab0905a8dd6600c6309b8d8a9cc2b14b8
- Size of remote file:
- 343 MB
- SHA256:
- 3855fd49c893b648195f420d379c1b239599414472ef2577c70c1d2cb5c60b41
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