Instructions to use ProbeX/Model-J__MAE__model_idx_0333 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_0333 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_0333") 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_0333") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__MAE__model_idx_0333", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f1b57895865918bb689c9f2c9ab2d74ade2569e946ecf0761c636eb429ade145
- Size of remote file:
- 5.37 kB
- SHA256:
- b6eef0c85b185fd695ef37afe5e0391fbe7f91454a58f77d430c1c68723b9152
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