Instructions to use ProbeX/Model-J__DINO__model_idx_0134 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_0134 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_0134") 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_0134") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__DINO__model_idx_0134", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 96ed34974249cf138237eda0fa8bb371ebaff215fdd09885e17ba9e0523d9432
- Size of remote file:
- 343 MB
- SHA256:
- 10e89011a596f7d1a83200d84656b25ee5373e23dab5e53809f3156f0fc848c7
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