Instructions to use bryandts/image_classification_face with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bryandts/image_classification_face with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="bryandts/image_classification_face") 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("bryandts/image_classification_face") model = AutoModelForImageClassification.from_pretrained("bryandts/image_classification_face", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from bryandts/image_classification_face: direct link, hf CLI and curl.
- Browser
- Download file 4.09 kB
-
https://huggingface.co/bryandts/image_classification_face/resolve/main/training_args.bin
- Command line
-
hf download hf://bryandts/image_classification_face/training_args.bin
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curl -L -o training_args.bin https://huggingface.co/bryandts/image_classification_face/resolve/main/training_args.bin
4.09 kB
- Xet hash:
- eca12bf377111c17ce62f22cf91856ba59123cf6ecb3aa29168ab613843da68f
- Size of remote file:
- 4.09 kB
- SHA256:
- 83c031794711208b349311a74b7be2b86c861da3d0701cc5c878bb9d709f933d
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