LowinLi/stable-diffusion-streamlit
Quantized stable-diffusion cutting down memory 75%, testing in streamlit, deploying in container
Implements ONNX Runtime quantization (INT8) to reduce Stable Diffusion v1.4 memory footprint from 5.2GB to 1.3GB while maintaining image quality, with negligible inference overhead. Wraps the quantized pipeline in a Streamlit web interface featuring real-time progress tracking via Python threading and a gallery view for generated outputs. Ships as a Docker container for straightforward deployment with configurable runtime parameters like sampling steps and guidance scale.
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54
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Language
Python
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Last pushed
Feb 07, 2026
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