Instructions to use dima806/fairface_age_image_detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dima806/fairface_age_image_detection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="dima806/fairface_age_image_detection") 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("dima806/fairface_age_image_detection") model = AutoModelForImageClassification.from_pretrained("dima806/fairface_age_image_detection", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 260d17406a8e7fc600848e3e9367a08f6e78841bd4c7dfa0e4cbb36f0e823192
- Size of remote file:
- 5.3 kB
- SHA256:
- 5ba8df84fa27b6ce1aa5fc9dad74c0fa9ee6fdec46d72d1f00235b986d4684db
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