Instructions to use Enverrr/gender_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Enverrr/gender_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Enverrr/gender_classification") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("Enverrr/gender_classification") model = AutoModelForImageClassification.from_pretrained("Enverrr/gender_classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Enverrr/gender_classification: direct link, hf CLI and curl.
- Browser
- Download file 343 MB
-
https://huggingface.co/Enverrr/gender_classification/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Enverrr/gender_classification/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Enverrr/gender_classification/resolve/main/pytorch_model.bin
343 MB
- Xet hash:
- c51baf15bff64014b0cc6a7e8e5cd70f5f2c5aa30f736f2febec701f1221d45a
- Size of remote file:
- 343 MB
- SHA256:
- f0e4f2cc7d71f2ecc145c2776a1d3212cf3dd5294c713e9bda7ccc5bfbbe9859
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