Instructions to use arpanl/models-moved with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use arpanl/models-moved with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="arpanl/models-moved") 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("arpanl/models-moved") model = AutoModelForImageClassification.from_pretrained("arpanl/models-moved", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from arpanl/models-moved: direct link, hf CLI and curl.
- Browser
- Download file 4.98 kB
-
https://huggingface.co/arpanl/models-moved/resolve/main/training_args.bin
- Command line
-
hf download hf://arpanl/models-moved/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/arpanl/models-moved/resolve/main/training_args.bin
4.98 kB
- Xet hash:
- fcf8f0c88b8271406a7b27b530bf1170be49ce4effc34be5a2b82165b9b7ddd4
- Size of remote file:
- 4.98 kB
- SHA256:
- 2ea348f3d5cf5a6e3d30c73e18d2765d988cfd7b5a11862de7204a55b30d51a2
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