Instructions to use ProbeX/Model-J__MAE__model_idx_0908 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_0908 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_0908") 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_0908") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__MAE__model_idx_0908") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a37abaa7e720f1bad001f09db77bc87c567f1383098c39705f3b484c451ff8b5
- Size of remote file:
- 5.37 kB
- SHA256:
- 71771b895d33fc0127b0cd2ee71aa2c4d52f11c8337c9cde42941ff8a88db031
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