Instructions to use ProbeX/Model-J__MAE__model_idx_0177 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_0177 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_0177") 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_0177") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__MAE__model_idx_0177", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2eee13a167eb274cdf93e8ad60aa33d3741cf4c47416673294336864dec8bf52
- Size of remote file:
- 5.37 kB
- SHA256:
- 65ae174f74398a35e8c96df21a39d39899ee51eea039931608e37a6a29edeb76
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