Instructions to use ProbeX/Model-J__MAE__model_idx_0291 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_0291 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_0291") 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_0291") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__MAE__model_idx_0291", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 605ecad97ba548b1561ba4138079c5d307fb54fe79fb69e812c4e07709c56331
- Size of remote file:
- 5.37 kB
- SHA256:
- bb68aa69140656f9913ef396700bc89654fa61357be3b0be690e59d923e8bef2
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