Instructions to use ProbeX/Model-J__MAE__model_idx_0297 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_0297 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_0297") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("ProbeX/Model-J__MAE__model_idx_0297") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__MAE__model_idx_0297", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from ProbeX/Model-J__MAE__model_idx_0297: direct link, hf CLI and curl.
- Browser
- Download file 5.37 kB
-
https://huggingface.co/ProbeX/Model-J__MAE__model_idx_0297/resolve/main/training_args.bin
- Command line
-
hf download hf://ProbeX/Model-J__MAE__model_idx_0297/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/ProbeX/Model-J__MAE__model_idx_0297/resolve/main/training_args.bin
5.37 kB
- Xet hash:
- 29332958a0a10e068fa2544bfe65a47f82f8e96a121c5d47749fdc6613aa02df
- Size of remote file:
- 5.37 kB
- SHA256:
- 52e3e9613a226b425411102bc527a3243389b2b9b9df1defc0d83b2b785f005c
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