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docs/source/model/StableDiffusionXL.md

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-# Stable Diffusion XL
+# Stable Diffusion XL
+
+## 相关链接
+
+* 论文：[High-Resolution Image Synthesis with Latent Diffusion Models](https://arxiv.org/abs/2307.01952)
+* 模型
+    * stable-diffusion-xl-base-1.0
+        * [HuggingFace](https://huggingface.co/stabilityai/stable-diffusion-xl-base-1.0)
+        * [ModelScope](https://modelscope.cn/models/AI-ModelScope/stable-diffusion-xl-base-1.0)
+
+
+## 模型介绍
+
+Stable Diffusion XL 与之前版本的 Stable Diffusion 相比，将 UNet 主干网络增大了三倍，SDXL 使用了两个文本编码器：([OpenCLIP-ViT/G](https://github.com/mlfoundations/open_clip) 和 [CLIP-ViT/L](https://github.com/openai/CLIP/tree/main))，因此在 UNet 中增加了更多的注意力模块和更大的交叉注意力上下文。我们设计了多种新颖的条件方案，并在多种宽高比上训练SDXL。同时 SDXL 引入了一个精细化模型 ，在后处理阶段来提高SDXL生成样本的逼真度。
+
+SXDL的模型结构如下：
+
+![](https://github.com/user-attachments/assets/1f94bbe3-a2f4-410b-9f68-d500bf91b0f0)
+
+
+## 代码样例
+
+```python
+from diffsynth import ModelManager, SDXLImagePipeline, download_models
+import torch
+
+
+# Download models (automatically)
+# `models/stable_diffusion_xl/bluePencilXL_v200.safetensors`: [link](https://civitai.com/api/download/models/245614?type=Model&format=SafeTensor&size=pruned&fp=fp16)
+download_models(["BluePencilXL_v200"])
+
+# Load models
+model_manager = ModelManager(torch_dtype=torch.float16, device="cuda")
+model_manager.load_models(["models/stable_diffusion_xl/bluePencilXL_v200.safetensors"])
+pipe = SDXLImagePipeline.from_model_manager(model_manager)
+
+prompt = "masterpiece, best quality, solo, long hair, wavy hair, silver hair, blue eyes, blue dress, medium breasts, dress, underwater, air bubble, floating hair, refraction, portrait,"
+negative_prompt = "worst quality, low quality, monochrome, zombie, interlocked fingers, Aissist, cleavage, nsfw,"
+
+torch.manual_seed(0)
+image = pipe(
+    prompt=prompt,
+    negative_prompt=negative_prompt,
+    cfg_scale=6,
+    height=1024, width=1024, num_inference_steps=60,
+)
+image.save("1024.jpg")
+
+```