Instructions to use ProbeX/Model-J__MAE__model_idx_0334 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_0334 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_0334") 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_0334") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__MAE__model_idx_0334", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fe939267c0f0ddc227d6b78c59d0c5ff5734fef87965cfd704fa448f323b9ec9
- Size of remote file:
- 5.37 kB
- SHA256:
- 28a46a77e0a49a3c52b63e1940e85ff73b9c41ff438dfea8f3d26fdf5768f693
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