Instructions to use ProbeX/Model-J__MAE__model_idx_0075 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_0075 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_0075") 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_0075") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__MAE__model_idx_0075", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 850790e81fbc3dd86fec87d950da9528d0b74fded58a62d0d9454d26c292594c
- Size of remote file:
- 5.37 kB
- SHA256:
- d990bd4fb486a21244e886ddef734ffb5a2b6239c1f4eef4597763a782753dc8
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