Instructions to use ProbeX/Model-J__MAE__model_idx_0845 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_0845 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_0845") 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_0845") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__MAE__model_idx_0845") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 430de99efe8c2fd1e956e8b3bb448bbb2e5ed1ad85496a4ba678a61c99d611d2
- Size of remote file:
- 5.37 kB
- SHA256:
- 3b552f51c1f26a68d18966ac1c5315362b6fff95fefd042956f277a9f3e6722b
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