Instructions to use ProbeX/Model-J__MAE__model_idx_0107 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_0107 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_0107") 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_0107") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__MAE__model_idx_0107", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e653a0ee5722483ae1f5d6ec67e6a9ec76e32ca8de0cce76b0513f45ba75e5a3
- Size of remote file:
- 343 MB
- SHA256:
- a45a0f7aeb8b0828505d456fc904666ed8f9440da9c88bd9f42ae4d358137d49
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