Instructions to use ProbeX/Model-J__MAE__model_idx_0497 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_0497 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_0497") 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_0497") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__MAE__model_idx_0497", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1c52e711bcc1ba56c23229cd12180cf499a82ab36861efdb6a2faf541f311d31
- Size of remote file:
- 5.37 kB
- SHA256:
- baa7bd5981b73c0d87ed822666735c505d25a0205e2887ecbdd04e624e926f91
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