Instructions to use ProbeX/Model-J__MAE__model_idx_0773 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_0773 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_0773") 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_0773") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__MAE__model_idx_0773", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ea2335f787b7c4b56d26f8edc1c60a3b156ea1c0aa6e7da76a0b2208219151ad
- Size of remote file:
- 5.37 kB
- SHA256:
- 10f72fed30246ae6cf7c92cff262418bd35f68cf8b40c52445851bf1e5dbb1b7
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