Instructions to use ProbeX/Model-J__MAE__model_idx_0854 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_0854 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_0854") 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_0854") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__MAE__model_idx_0854", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a5b5914f4a7e691e2328492b1bbd75be0ff6f6e336b8f724fd5bce473f4690e8
- Size of remote file:
- 5.37 kB
- SHA256:
- 6d7f2ee390a4bddb8d69b26a4c2e59b2fee67f2ef2fa8f902ff4450015687b55
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