Image Classification
Transformers
PyTorch
TensorBoard
Safetensors
vit
huggingpics
Eval Results (legacy)
Instructions to use rizvandwiki/gender-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rizvandwiki/gender-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="rizvandwiki/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("rizvandwiki/gender-classification") model = AutoModelForImageClassification.from_pretrained("rizvandwiki/gender-classification", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from rizvandwiki/gender-classification: direct link, hf CLI and curl.
- Browser
- Download file 343 MB
-
https://huggingface.co/rizvandwiki/gender-classification/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://rizvandwiki/gender-classification/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/rizvandwiki/gender-classification/resolve/main/pytorch_model.bin
343 MB
- Xet hash:
- 4d6aeb0e4c22adccb3d930589aa2977c9c7fdbe755878184553846044380f4b0
- Size of remote file:
- 343 MB
- SHA256:
- 049c8ee0e89288713cbc6c9f65ee285560c31ec438b09799fa0198484cd43966
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