Instructions to use ProbeX/Model-J__MAE__model_idx_0149 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_0149 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_0149") 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_0149") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__MAE__model_idx_0149") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6404334666e9abf306878a4bae1a777d19ae48bec07d425e11260f8ddc572d3d
- Size of remote file:
- 5.37 kB
- SHA256:
- fc07f4dd0d6ae0b57294d82d20c72158d398e385718d03cf099bda1966a36501
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