Instructions to use ProbeX/Model-J__MAE__model_idx_0646 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_0646 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_0646") 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_0646") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__MAE__model_idx_0646", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c63a8e6f9889a63486c5dac4be1c45f1505c93857cd3b0c0f9a8ecf18ae571e4
- Size of remote file:
- 5.37 kB
- SHA256:
- ef60aacb5d282281021978addbe9ef746174c7fd047647dc3ea27c9161ae6ecc
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