Instructions to use ProbeX/Model-J__MAE__model_idx_0061 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_0061 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_0061") 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_0061") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__MAE__model_idx_0061", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e6136aa8922fc9ed928bf736e70efe646b15a19c17ccb509908b02cd75f69b74
- Size of remote file:
- 5.37 kB
- SHA256:
- 896c7d134fb02a959f7e1056873c6bee3991de44d33fa0ffde9372d85053dcbc
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