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Open Source Model Profile · rizvandwiki

gender-classification

Gender-classification is an 85.80M-parameter ViT image classifier from rizvandwiki. According to the model card, it is a HuggingPics-autogenerated female-male classifier.

Publisher
rizvandwiki
Task
image-classification
Model type
vit
License
Unknown
Library
transformers
Publication status
Accepted · not indexed

Model overview

Gender-classification is published by rizvandwiki as an image-classification model. Captured configuration identifies ViTForImageClassification with model type vit, and Safetensors metadata reports 85,800,194 parameters. According to the model card, it was autogenerated by HuggingPics with a linked Colab demo for building custom image classifiers.

Recorded capabilities

Female-male image classification

According to the model card, this HuggingPics-autogenerated classifier uses female and male example images.

ViT classifier at 85.80M scale

Captured configuration identifies ViTForImageClassification, with Safetensors metadata reporting 85,800,194 parameters.

Transformers image-classification record

The hub record lists the transformers library with PyTorch, safetensors, vit, and endpoints-compatible tags.

Use cases in the source record

  • Binary female-male image classification with the HuggingPics-generated classifier, following the publisher's demo pattern.

Limitations and unknowns

  • No license value was extracted from the current evidence.
  • No training dataset, evaluation results, or accuracy figures were extracted from this record.
  • Provider state is historical snapshot data, not independently refreshed current availability.

Source and provenance

Source: rizvandwiki/gender-classification

Captured: Unknown. Processed: 2026-09-07T19:34:56.825629+00:00.

gender-classification Autogenerated by HuggingPics🤗🖼️ Create your own image classifier for anything by running the demo on Google Colab . Report any issues with the demo at the github repo . Example Images female male

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