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Qwen-Image-Edit-2511-Lightning

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Duplicate from lightx2v/Qwen-Image-Edit-2511-Lightning

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Co-authored-by: Lightx2v <lightx2v@users.noreply.huggingface.co>

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+ ---
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+ license: apache-2.0
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+ tags:
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+ - diffusion-single-file
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+ - comfyui
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+ - distillation
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+ - LoRA
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+ - lora
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+ - Qwen-Image
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+ - Qwen-Image-Edit
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+ base_model:
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+ - Qwen/Qwen-Image-Edit-2511
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+ pipeline_tags:
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+ - image-to-image
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+ - text-to-image
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+ library_name: diffusers
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+ pipeline_tag: image-to-image
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+ ---
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+ # Qwen-Image-Edit-2511-Lightning
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+
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+ ## Model Overview
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+ Qwen-Image-Edit-2511-Lightning is a collection of optimized models tailored for image editing tasks, leveraging step distillation and quantization techniques to deliver high-efficiency inference performance. This repository hosts three core model files with distinct characteristics:
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+
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+ | Model File Name | Type | Key Features |
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+ |-----------------|------|--------------|
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+ | `Qwen-Image-Edit-2511-Lightning-4steps-V1.0-bf16.safetensors` | 4-step Distilled LoRA | BF16 precision, lightweight, 4-step inference |
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+ | `Qwen-Image-Edit-2511-Lightning-4steps-V1.0-fp32.safetensors` | 4-step Distilled LoRA | FP32 precision, high accuracy, 4-step inference |
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+ | `qwen_image_edit_2511_fp8_e4m3fn_scaled_lightning.safetensors` | FP8 Quantized | FP8 (e4m3fn scaled) precision, fused with 4-step distilled LoRA, optimized for low-memory deployment |
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+
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+ ## Usage Instructions
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+ This model suite supports two mainstream usage frameworks, with detailed guides provided below:
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+
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+ ### 1. Qwen-Image-Lightning Framework
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+ For full documentation on model usage within the Qwen-Image-Lightning ecosystem (including environment setup, inference pipelines, and customization), please refer to:
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+ [Qwen-Image-Lightning GitHub Repository](https://github.com/ModelTC/Qwen-Image-Lightning/)
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+
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+ ### 2. LightX2V Framework
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+ The models are fully compatible with the LightX2V lightweight video/image generation inference framework. For step-by-step usage examples, configuration templates, and performance optimization tips, see:
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+ [LightX2V Qwen Image Edit Documentation](https://github.com/ModelTC/LightX2V/blob/main/examples/qwen_image/README.md)
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+
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+ ## Key Optimizations
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+ - **Step Distillation**: The LoRA models reduce the original inference steps to just 4 steps, achieving significant speedup (≈10x faster than standard 40-step inference) while preserving image editing quality.
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+ - **FP8 Quantization**: The quantized base model balances performance and resource efficiency, reducing GPU memory usage by ~50% compared to FP32 while maintaining editing fidelity.
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+
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+ ## Support
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+ For technical issues, feature requests, or integration questions:
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+ - Open an issue in the [Qwen-Image-Lightning repo](https://github.com/ModelTC/Qwen-Image-Lightning/issues) (for Qwen framework-specific questions)
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+ - Open an issue in the [LightX2V repo](https://github.com/ModelTC/LightX2V/issues) (for LightX2V integration questions)
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