Instructions to use dima806/attractive_faces_celebs_detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dima806/attractive_faces_celebs_detection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="dima806/attractive_faces_celebs_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/attractive_faces_celebs_detection") model = AutoModelForImageClassification.from_pretrained("dima806/attractive_faces_celebs_detection", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ec43f74e83b366020138c45046eb3c16905d2ea3edd7059dc43de68ad46f187a
- Size of remote file:
- 343 MB
- SHA256:
- 5bde3e2c80fae1efe75d48d331cd155459a08b7d8d71abba59608dc26e52971a
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