Image Classification
Transformers
PyTorch
TensorBoard
Safetensors
vit
huggingpics
Eval Results (legacy)
Instructions to use rizvandwiki/gender-classification-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rizvandwiki/gender-classification-2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="rizvandwiki/gender-classification-2") 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("rizvandwiki/gender-classification-2") model = AutoModelForImageClassification.from_pretrained("rizvandwiki/gender-classification-2") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 40be2e6a5766d0da342efcf154b381803099b4e73c4f6b4154fa4f72846352da
- Size of remote file:
- 343 MB
- SHA256:
- 715a9b7b4602c816c5b6e3679fb08b688ad8d43d3758200a6953ae61f871840f
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.