Instructions to use ProbeX/Model-J__MAE__model_idx_0344 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_0344 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_0344") 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_0344") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__MAE__model_idx_0344", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5f69e34efe24ab7279500fa0b6126668d8b0d36e09bdb91e29db3dfeb45a5d56
- Size of remote file:
- 5.37 kB
- SHA256:
- 77584ff1cd8280f48546cf792ae252db5495711e980015912edfff964829f66e
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