update readme

README.md

@@ -81,7 +81,7 @@ from lyrasd_model import LyraSdTxt2ImgPipeline
 # LyraSD 的 C++ 编译动态链接库，其中包含 C++ CUDA 计算的细节
 lib_path = "./lyrasd_model/lyrasd_lib/libth_lyrasd_cu11_sm80.so"
 model_path = "./models/lyrasd_rev_animated"
-lora_path = "./models/lyrasd_xiaorenshu_lora"
+lora_path = "./models/xiaorenshu.safetensors"
 
 # 构建 Txt2Img 的 Pipeline
 model = LyraSdTxt2ImgPipeline(model_path, lib_path)
@@ -130,14 +130,14 @@ from lyrasd_model import LyraSdXLTxt2ImgPipeline
 # LyraSD 的 C++ 编译动态链接库，其中包含 C++ CUDA 计算的细节
 lib_path = "./lyrasd_model/lyrasd_lib/libth_lyrasd_cu11_sm80.so"
 model_path = "./models/lyrasd_helloworldSDXL20Fp16"
-lora_path = "./models/lyrasd_xiaorenshu_lora"
+lora_path = "./models/dissolve_sdxl.safetensors"
 
 # 构建 Txt2Img 的 Pipeline
 model = LyraSdXLTxt2ImgPipeline(model_path, lib_path)
 
 # load lora
 # lora model path, name，lora strength
-model.load_lora_v2(lora_path, "xiaorenshu", 0.4)
+model.load_lora_v2(lora_path, "dissolve_sdxl", 0.4)
 
 # 准备应用的输入和超参数
 prompt = "a cat, cute, cartoon, concise, traditional, chinese painting, Tang and Song Dynasties, masterpiece, 4k, 8k, UHD, best quality"
@@ -165,7 +165,7 @@ for i, image in enumerate(images):
     image.save(f"outputs/res_txt2img_xl_lora_{i}.png")
 
 # unload lora，参数为 lora 的名字，是否清除 lora 缓存
-model.unload_lora_v2("xiaorenshu", True)
+model.unload_lora_v2("dissolve_sdxl", True)
 ```
 
 ## Demo output