Instructions to use ProbeX/Model-J__MAE__model_idx_0859 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ProbeX/Model-J__MAE__model_idx_0859 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="ProbeX/Model-J__MAE__model_idx_0859") 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__MAE__model_idx_0859") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__MAE__model_idx_0859", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6aeb22b75583b03785f1ab43eaae8c3c5ef2e4e98e441856c8cd8dfd38921159
- Size of remote file:
- 5.37 kB
- SHA256:
- d274a1b64033f237f91bfc87eef841714820eec73518776223c13a3247be3886
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