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 pytorch_model.bin from bryandts/image_classification_face: direct link, hf CLI and curl.
- Browser
- Download file 343 MB
-
https://huggingface.co/bryandts/image_classification_face/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://bryandts/image_classification_face/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/bryandts/image_classification_face/resolve/main/pytorch_model.bin
343 MB
- Xet hash:
- 7a91668611ebf07b598fed7061155368b8c16c5f24a61ee1e87bb7913b9afa09
- Size of remote file:
- 343 MB
- SHA256:
- 538c654685f112cfa4e59895f81bc82b5649ad9eeeda587d388b35954a569528
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