Instructions to use ProbeX/Model-J__MAE__model_idx_0140 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_0140 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_0140") 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_0140") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__MAE__model_idx_0140", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2e947b311aa78eb87723989fb6c924e3cb509cd90e9225ee1189e988ccdbcacd
- Size of remote file:
- 5.37 kB
- SHA256:
- a36ac72ea8389ff1bd6da6f7a3c02a77166425369c935f5d5914b731a0c3ce0b
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