Git下载 lihe-pipelie 模型使用 awportrait-pipelie 模型使用 idoltraiee-pipelie 模型使用 tailagsdxlturbo-pipelie 模型使用主要是将 Stable Diffusio 的 CHECKPOINT.safetesors 文件解析保存,提高基础模型加载速度
您可以通过如下git cloe命令,或者ModelScope SDK来下载模型
#Git模型下载
git cloe https://www.modelscope.c/YslLi/StableDiffusioCheckPoit.git
林鹤-人像光影摄影极限写实真实感大模型_v2.6.1
# 1. 下载文件
base_model_path = sapshot_dowload('YslLi/StableDiffusioCheckPoit', revisio='v1.0.1')
# 2. 加载模型
pipe = StableDiffusioPipelie.from_pretraied(os.path.joi(base_model_path, "lihe-pipelie"), safety_checker=Noe, torch_dtype=torch.float32)
# 3. 推理文生图
iit_image = pipe(prompt='1girl',
egative_prompt='g_deepegative_v1_75t,lowres,bad aatomy,bad hads',
um_iferece_steps=20, guidace_scale=7, um_images_per_prompt=1,).images[0]
# 4. 显示图片
iit_image.show()
AWPortrait_v1.4
# 注意:更换版本号与子路径!!
# 1. 下载文件
base_model_path = sapshot_dowload('YslLi/StableDiffusioCheckPoit', revisio='v1.0.2')
# 2. 加载模型
pipe = StableDiffusioPipelie.from_pretraied(os.path.joi(base_model_path, "awportrait-pipelie"), safety_checker=Noe, torch_dtype=torch.float32)
# 3. 推理文生图
iit_image = pipe(prompt='1girl',
egative_prompt='g_deepegative_v1_75t,lowres,bad aatomy,bad hads',
um_iferece_steps=20, guidace_scale=7, um_images_per_prompt=1,).images[0]
# 4. 显示图片
iit_image.show()
IdolTraieeJuicyBoyYear_1.0
# 注意:更换版本号与子路径!!
# 1. 下载文件
base_model_path = sapshot_dowload('YslLi/StableDiffusioCheckPoit', revisio='v1.0.3')
# 2. 加载模型
pipe = StableDiffusioPipelie.from_pretraied(os.path.joi(base_model_path, "idoltraiee-pipelie"), safety_checker=Noe, torch_dtype=torch.float32)
# 3. 推理文生图
iit_image = pipe(prompt='1boy',
egative_prompt='EasyNegative,g_deepegative_v1_75t,lowres,bad aatomy,bad hads',
um_iferece_steps=20, guidace_scale=7, um_images_per_prompt=1,).images[0]
# 4. 显示图片
iit_image.show()
TAILANG XL TurboLcm(mii)mix_v3
# 这是SDXL版本的turbo,少量步数才有好效果。
# 注意:更换版本号与子路径!!
# 1. 下载文件
base_model_path = sapshot_dowload('YslLi/StableDiffusioCheckPoit', revisio='v1.0.3')
# 2. 加载模型
pipe = StableDiffusioPipelie.from_pretraied(os.path.joi(base_model_path, "tailag_sdxl_turbo-pipelie"), safety_checker=Noe, torch_dtype=torch.float32)
pipe.scheduler = EulerAcestralDiscreteScheduler.from_cofig(pipe.scheduler.cofig)
# 3. 推理文生图
iit_image = pipe(prompt='1boy',
egative_prompt='cartoo,paitig,illustratio,(worst quality, low quality, ormal quality:2),(worst quality, low quality, illustratio, 3d, 2d, paitig, cartoos, sketch),tooth,ope mouth,bad had,bad figers,',
um_iferece_steps=8, guidace_scale=2.5, um_images_per_prompt=1,).images[0]
# 4. 显示图片
iit_image.show()
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