Overview

This image-classification model provides a streamlined solution for gender detection within visual datasets. Designed for developers building demographic analysis tools or personalized user experiences, it maps image inputs to gender categories with a lightweight footprint. Unlike general-purpose vision transformers, this specialized model is optimized for a single task, reducing inference latency and computational overhead. Integration is straightforward for those working within standard image-processing pipelines, making it a practical choice for augmenting metadata in large-scale media libraries or automating user profiling in application onboarding flows.

Highlights

Specialized image-classification for efficient gender detection
Low-latency inference ideal for real-time applications
Apache-2.0 license ensures flexible commercial integration
Simplifies demographic data extraction from visual assets

Usage

Install

# Install Hugging Face transformers
pip install transformers torch

SDK Usage

# Load model with transformers
from transformers import AutoModel, AutoTokenizer

model = AutoModel.from_pretrained("rizvandwiki/gender-classification")
tokenizer = AutoTokenizer.from_pretrained("rizvandwiki/gender-classification")

Hugging Face Download

We recommend downloading the model via the Hugging Face CLI or Hub SDK.

Guidance：Before downloading, install huggingface_hub with:

Guidance

pip install -U huggingface_hub

CLI Download

Download the full repository

huggingface-cli download rizvandwiki/gender-classification

Download a single file to a local folder (e.g. config.json into ./dir)

huggingface-cli download rizvandwiki/gender-classification config.json --local-dir ./dir

See the official docs for more CLI options

SDK Download

# 模型下载
from huggingface_hub import snapshot_download
model_dir = snapshot_download('rizvandwiki/gender-classification')

Git Download

Make sure git-lfs is installed first

Git Download

git lfs install
git clone https://huggingface.co/rizvandwiki/gender-classification

To skip LFS large-file downloads, use:

Skip LFS

GIT_LFS_SKIP_SMUDGE=1 git clone https://huggingface.co/rizvandwiki/gender-classification

Model files are hosted on the Hugging Face Hub — download directly via HF CLI / SDK / Git, not through this site.

PyTorch / Transformers Usage

Install Transformers

pip install -U transformers torch

Load the model and run inference

from transformers import AutoModelForCausalLM, AutoTokenizer

model = AutoModelForCausalLM.from_pretrained('rizvandwiki/gender-classification')
tokenizer = AutoTokenizer.from_pretrained('rizvandwiki/gender-classification')

Full Documentation

来源: HuggingFace

---
tags:

image-classification

pytorch

huggingpics

metrics:

accuracy

model-index:

name: gender-classification

results:
- task:
name: Image Classification
type: image-classification
metrics:
- name: Accuracy
type: accuracy
value: 0.9244444370269775
---