Instructions to use ProbeX/Model-J__MAE__model_idx_0394 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_0394 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_0394") 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_0394") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__MAE__model_idx_0394") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9f28e28ac0eb368b187b85032380b389dba694f31b1e3b5f2c479dd2cb84cb50
- Size of remote file:
- 343 MB
- SHA256:
- 86cdb63cdba0943abafe81188f08eb0efbb2f02586da3f0c5b814504988d43bb
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