Instructions to use ProbeX/Model-J__MAE__model_idx_0249 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_0249 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_0249") 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_0249") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__MAE__model_idx_0249", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4d9d1e65262ff149a95bb69310040a6d9e1928639a07ab853ab2197eac6f42c8
- Size of remote file:
- 343 MB
- SHA256:
- b15cbfb53e0b2c6df98da760452d1380c1fb7c108aec156adce70e60b7b63aa9
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