Instructions to use ProbeX/Model-J__MAE__model_idx_0320 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_0320 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_0320") 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_0320") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__MAE__model_idx_0320", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 54ac85f23fd38d85d972717bdb218f39e2fe150cf28ebfc5de8a5fd7f3161b2b
- Size of remote file:
- 5.37 kB
- SHA256:
- 4ab8110f41e9e205ff42f8ed82b978be232805231712c97c43063a0147461f39
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