Instructions to use ProbeX/Model-J__MAE__model_idx_0696 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_0696 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_0696") 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_0696") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__MAE__model_idx_0696", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 20a64008aa6b040414e69e923a5692075a2524d3ef990187f3b83b63888ef0b9
- Size of remote file:
- 5.37 kB
- SHA256:
- 6ec83d404bd44d55ad924e7f38e8cdd3a32103685b170d6f1678e12786658e31
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