Instructions to use ProbeX/Model-J__MAE__model_idx_0055 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_0055 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_0055") 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_0055") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__MAE__model_idx_0055", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 81d66294cfcef0f6fa2c249f058178fec43c28654be550c7c693467c90e75d7a
- Size of remote file:
- 5.37 kB
- SHA256:
- 3716fe6ef5a17c130b56a867d227aebd661c9ea2a316c1d6da3b71d01747c6ca
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