Instructions to use ProbeX/Model-J__MAE__model_idx_0855 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_0855 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_0855") 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_0855") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__MAE__model_idx_0855", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9d47025300b6f4667a9a4a16bf68d9d5b50f492fddf606b5e911e67856fcbcc4
- Size of remote file:
- 5.37 kB
- SHA256:
- eac1458dbc933c6525de2d57391e85f0ff259e96f282e8a9ca34c05a4f51e670
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