Instructions to use glazzova/body_complexion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use glazzova/body_complexion with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="glazzova/body_complexion") 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("glazzova/body_complexion") model = AutoModelForImageClassification.from_pretrained("glazzova/body_complexion", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a05df17df90f9376eff1bb1eee17b1920f734955fe4085f960783cfbec0b63fe
- Size of remote file:
- 188 MB
- SHA256:
- 3546e497a314a5a0854beb747efe074fcdf7eb96e7c8ce9fc2b0ba889ea93de0
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