Instructions to use ProbeX/Model-J__MAE__model_idx_0512 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_0512 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_0512") 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_0512") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__MAE__model_idx_0512", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- aae82046e51d4937e081f0f75957358d7d9913e669f17b24b5b9c73fed13fcac
- Size of remote file:
- 5.37 kB
- SHA256:
- b26aa4f417ec53d48cca853655899d2ea3be3f68e85526326b5248e7cbe68b43
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