Instructions to use ProbeX/Model-J__MAE__model_idx_0453 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_0453 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_0453") 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_0453") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__MAE__model_idx_0453", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bd23ce56992b0b96762edd354e3d20bf2277c36ddf067d3e2beedc5536c2a902
- Size of remote file:
- 5.37 kB
- SHA256:
- fac6be1429af4535948a8ce8d40ebf91311a8182466467fd5254abde7501a994
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