Instructions to use ProjectPersonal/GenderClassifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ProjectPersonal/GenderClassifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="ProjectPersonal/GenderClassifier") 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("ProjectPersonal/GenderClassifier") model = AutoModelForImageClassification.from_pretrained("ProjectPersonal/GenderClassifier") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3584cd24ac47fae1e10800f0e249ecdc9a173a06736c65ad07e99316c4d09722
- Size of remote file:
- 343 MB
- SHA256:
- 3bf8c5ef29e34310011e6bf288d7178536579815262765b1e69793ab1b9e0428
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