Instructions to use ProbeX/Model-J__MAE__model_idx_0394 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_0394 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_0394") 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_0394") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__MAE__model_idx_0394") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 43b93867303af15f746c30289b52ebae281cdc5dcb33b88901f2f251f81ef02b
- Size of remote file:
- 5.37 kB
- SHA256:
- d710ef3b2c487a256a18bbfc7dda5da9534af4374cca2b4af7f26d8f518e88bb
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