Instructions to use ProbeX/Model-J__MAE__model_idx_0174 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_0174 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_0174") 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_0174") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__MAE__model_idx_0174", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 09a8a388fb8dc4b5add4d6e63108ebb5a76c00df5427162376cca17d39a9019c
- Size of remote file:
- 5.37 kB
- SHA256:
- 2c54aacf7507f09347c4af01f1711529807e9a4390bc8062c1c1dd37a733be00
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