Instructions to use ProbeX/Model-J__MAE__model_idx_0947 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_0947 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_0947") 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_0947") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__MAE__model_idx_0947", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1662e999d1a319f1b5b7ad63c5eaa998e88bf30e0b7854df4691d63fdde8dbcc
- Size of remote file:
- 5.37 kB
- SHA256:
- ab4a427dffda669f2c4dbd0862cd59ce93337cd10c9498e37be98c52d62c6cd2
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