Instructions to use ProbeX/Model-J__MAE__model_idx_0749 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_0749 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_0749") 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_0749") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__MAE__model_idx_0749") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e15f317ebb11eadc8bb74a6b017c2b1ce41fbb4684af80efe7f369653bcd2dff
- Size of remote file:
- 5.37 kB
- SHA256:
- c8b4eb533374595ff77acf8e32a9bb7cffb3bf853774da5f79b57efe50fdbca9
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