Instructions to use ProbeX/Model-J__MAE__model_idx_0421 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_0421 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_0421") 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_0421") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__MAE__model_idx_0421", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 984c38c658f80ffe30529965dc29c50240defbbd0b6c65d02340ac429032ca90
- Size of remote file:
- 5.37 kB
- SHA256:
- 54f8a05a6d00bc74d890df26a9812a62f34ed11da9f1c2d2e190fab5eb27d437
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