Quen最强大的开源图像生成模型
概览
& nbsp; & nbsp; & nbsp; & nbsp; & nbsp; \\ HuggingFace & nbsp; & nbsp; & nbsp; & nbsp;\\ Blog & nbsp; & nbsp;\ & nbsp;\\ & nbsp;\\ & nbsp;\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\ 我们很兴奋开放源代码, 用Just (32 Single-Stream DiT分层),Quen-Image-2.1平衡生成质量,推论效率,多功能. 四个关键改进定义了此发布: -)- 一种具有相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相相 - 从文本中生成定期或透明的(RGBA)图像,编辑透明的图层,从相片中取出主题——都是在一个模型中. - 支持最多,通过圆圈、涂上说明或单独的口罩指定本地编辑,并为人员和产品保留身份.
概述（AI 翻译）
& nbsp; & nbsp; {}\ 模型范围 \\ huggingFace \\ \\ Blog \\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\ \ demo \nbsp;\\ \\ Discord \\\\\\\\\\\\\\\\\\> \\ WeChat
□ 导言
我们对开源QQWEN-Image-2.1感到兴奋,这是Quen家族中统一的文本到图像生成和图像编辑模式. 在其视觉生成组件(32 Single-Stream DiT层)中只有**7B参数,Quen-Image-2.1平衡了生成质量,推论效率,多功能.
四个关键改进定义了此发布:
- ** 压缩和高效**——一种轻量级结构,具有混合角性注意和前缀KV缓存再利用,以低计算成本提供强图像质量.
- ** 自然透明、统一创建和编辑**——从文本中生成定期或透明的(RGBA)图像,编辑透明的分层,从相片中取出主题——都用一个模型。
- ** 虚拟编辑**——最多支持10个参考图像,通过圆圈指定本地编辑,涂上说明或单独的口罩,并为个人和产品保留身份.
本页由 AI 翻译，技术细节请以原文为准。
README
以下为原文 README 节选，完整内容请查看原文。
🤖 ModelScope | 🤗 HuggingFace | 📑 Blog | 🖥️ Demo | 🫨 Discord | 💬 WeChat
Introduction
We are excited to open-source Qwen-Image-2.1, a unified text-to-image generation and image editing model in the Qwen family. With just 7B parameters in its visual generation component (32 Single-Stream DiT layers), Qwen-Image-2.1 balances generation quality, inference efficiency, and versatility.
Four key improvements define this release:
- Compact and Efficient — A lightweight architecture with mixed-granularity attention and prefix KV cache reuse delivers strong image quality at low computational cost.
- Native Transparency, Unified Creation and Editing — Generate regular or transparent (RGBA) images from text, edit transparent layers, and extract subjects from photographs—all in one model.
- Versatile Editing — Support up to 10 reference images, specify local edits via circles, painted annotations, or separate masks, and preserve identity for people and products.
- Realistic Textures and Refined Aesthetics — Improved typography, portrait lighting, and fine details for more visually compelling results.
News
- 2026.10.09: We released Qwen-Image-2.1-Turbo for image generation and editing in just 8 denoising steps. Get started with the Turbo example below.
- 2026.10.09: Qwen-Image-2.1 Pro and Turbo APIs are now officially live! Explore the Pro API and Turbo API on Alibaba Cloud Model Studio.
- 2026.09.20: We released Qwen-Image-2.1! Check our Blog for more details. Weights available at HuggingFace and ModelScope.
安装
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