r: int, lora_alpha: int, lora_dropout: float, merge_weights: bool, ): ...
对比两个库训练后保存下来的权重文件,我发现sd-scripts训练后存下来的权重中,除了有每层LoRA的两个低秩矩阵以外,还保存了每层的alpha值,而diffusers保存下来的文件是没有alpha值的。 训练后使用diffusers推理时,通常会使用pipeline.load_lora_weights将LoRA权重加载到基模,再用pipeline.set_adapters(name, weight)指定...
CLIPTextModelWithProjection, CLIPTokenizer# 从本地模块导入图像处理和加载器类from...image_processorimportPipelineImageInput, VaeImageProcessorfrom...loadersimportFromSingleFileMixin, StableDiffusionXLLoraLoaderMixin, TextualInversionLoaderMixin# 从本地模型导入相关类from...modelsimportAuto...
from diffusers import DiffusionPipeline pipeline = DiffusionPipeline.from_pretrained( "runwayml/stable-diffusion-v1-5" ) lora_path = "./lora_dir" pipeline.load_lora_weights(pretrained_model_name, use_safetensors=True, weight_name="lora_name.safetensors") 注意,这张方式,最大的问题是不能像sd...
My trained lora is here. It only finetunes the unet backbone. When I use flux_pipe.load_lora_weights('./lora/', weight_name='dog_and_cat_special_key.safetensors'), it doesn't take effect. I debug the code, inside the load_lora_weights method: def load_lora_weights( self, pretra...
diffusers_name.replace(dora_scale_key_to_replace_te,".lora_magnitude_vector.") ] = state_dict.pop(key.replace("lora_down.weight","dora_scale"))# 如果存在 alpha,则存储iflora_name_alphainstate_dict: alpha = state_dict.pop(lora_name_alpha).item()# 更新网络中的 alpha 名称network_alphas....
("marinalaurel/vintage_street", weight_name="Vintage_Street_Photo.safetensors", adapter_name="street") 2 pipe.load_lora_weights("marinalaurel/Polyhedron_LightingSDXL_Chiaroscuro", weight_name="polyhedron_chiaroscuro-000005.safetensors", adapter_name="light") 3 pipe.set_adapters(["street", "...
├── step999|└── pytorch_lora_weights.bin # weightforinferencingwithdiffusers.pipeline ├── iter_1000.pth # checkpoint from each step ├── last_checkpoint # last checkpoint,it can be usedforresuming └── stable_diffusion_v15_dreambooth_lora_dog.py # latest config file ...
Support convert LoRA safetensors into diffusers format by @haofanwang in #2403 [Unet1d] correct docs by @patrickvonplaten in #2565 [Training] Fix tensorboard typo by @patrickvonplaten in #2566 allow Attend-and-excite pipeline work with different image sizes by @yiyixuxu in #2476 ...
pipe.load_ip_adapter("h94/IP-Adapter", subfolder="models", weight_name="ip-adapter_sd15.bin") pipe.load_lora_weights(lcm_lora_id) pipe.scheduler = LCMScheduler.from_config(pipe.scheduler.config) pipe.enable_model_cpu_offload()