Instructions to use ProbeX/Model-J__MAE__model_idx_0417 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_0417 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_0417") 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_0417") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__MAE__model_idx_0417", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 91c88a176f8d422cd96b99466ecf39b0e9beeb6996bba005e001ca81188159e9
- Size of remote file:
- 5.37 kB
- SHA256:
- 907a67575f8db8ee1118924ad3f884f312e1421296511f9821e418c08e05a14f
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