Instructions to use ProbeX/Model-J__MAE__model_idx_0400 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_0400 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_0400") 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_0400") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__MAE__model_idx_0400", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a34147ed05dce676bfb21255caceacd11e7c6bc165e087a0e3a5eedf62a29e54
- Size of remote file:
- 5.37 kB
- SHA256:
- 4bc2ab3480f1412c1d5f3ea0163cdd8a19e081ce8f459e34dffb03f8c2409d58
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