Instructions to use Leilab/gender_class with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Leilab/gender_class with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Leilab/gender_class") 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("Leilab/gender_class") model = AutoModelForImageClassification.from_pretrained("Leilab/gender_class") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 36319419c999ed31e4ebfc7186c3c48524ef3daad72d395e5d1674ef32676b5b
- Size of remote file:
- 343 MB
- SHA256:
- 82a61c82e5dfb89c648a0b370211f5957a5d6fff226bebc60e1b8eec48474f8e
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.