Instructions to use ProbeX/Model-J__MAE__model_idx_0607 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_0607 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_0607") 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_0607") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__MAE__model_idx_0607", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 30412b9b964fba61ae6f1c357a65495c7b81f463bf1532f484d710034820ee51
- Size of remote file:
- 5.37 kB
- SHA256:
- 575040d8f6d1813185fede7b8e688261efc2779052b715c40b348bdc29e739ef
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