Instructions to use ProbeX/Model-J__MAE__model_idx_0806 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_0806 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_0806") 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_0806") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__MAE__model_idx_0806", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9a5e39c96eae5e095a67bfccbeb9d9c1b3d8ea43e22ec75e92c5f0808d51e5ec
- Size of remote file:
- 5.37 kB
- SHA256:
- 5497689456cb6f9f44fa2b43a5478f21e80be07ba858629683fb3d30f47abf5d
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