Instructions to use ProbeX/Model-J__MAE__model_idx_0721 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_0721 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_0721") 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_0721") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__MAE__model_idx_0721", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fd49b33246e04d75019cbd8ac66ce4b6a24c7f3870b5ed96baacdb2fac739943
- Size of remote file:
- 5.37 kB
- SHA256:
- 885493f90ccf52fbdd28e92f060c7656c72a1fafd3ed8f0a8f7f0df6e93aea7a
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