Instructions to use ProbeX/Model-J__MAE__model_idx_0825 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_0825 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_0825") 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_0825") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__MAE__model_idx_0825", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5498701495d11b9ed0c0398ab4d29cfb7d718b1d9ee773de30009497f5bac9d2
- Size of remote file:
- 5.37 kB
- SHA256:
- bf9d92fe900f08a2fcea6dd8cdf4ea4d10cba7ff8191045bb8bd19d22dc76492
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