Instructions to use ProbeX/Model-J__MAE__model_idx_0540 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_0540 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_0540") 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_0540") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__MAE__model_idx_0540", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2bc459bd855b22c3e95e0cca46ed840b913c0c4c8474229fd6163ecd4aa1c74e
- Size of remote file:
- 5.37 kB
- SHA256:
- de833db64ddea3a0468090f0c65fc7a7a697c661ec0e1504e2ce44f0f215b6c3
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