Instructions to use ProbeX/Model-J__MAE__model_idx_0305 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_0305 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_0305") 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_0305") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__MAE__model_idx_0305", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 30321c7ad2679a17d76d0a3dc41538061fb38f76b3fca613d89e35d6a320ecee
- Size of remote file:
- 5.37 kB
- SHA256:
- d874967ac2d6bc4930a649535b9453ae954814ecff6221b79e3cf2c84396b01a
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