pipe = StableDiffusionPipeline.from_single_file( model_path, use_safetensors=True, torch_dtype=torch.float16, variant="fp16", safety_checker=None )试试看还会不会报错，应该没问题了。
Stable Diffusion 3.5 的 transformer 模型还可以使用 Stability AI 发布的原生参数文件来进行初始化 。这里需要使用 from_single_file 方法:import torchfrom diffusers import SD3Transformer2DModel, StableDiffusion3Pipelinetransformer = SD3Transformer2DModel.from_single_file("https://huggingface.co/stabilityai/...
# XFormers 注意力处理器)from...models.loraimportadjust_lora_scale_text_encoder# 调整文本编码器的 LoRA 比例from...schedulersimportKarrasDiffusionSchedulers# Karras 扩散调度器from...utilsimport(
Stable Diffusion 3.5 的 transformer 模型还可以使用 Stability AI 发布的原生参数文件来进行初始化 。 这里需要使用from_single_file方法: import torch from diffusers import SD3Transformer2DModel, StableDiffusion3Pipeline transformer = SD3Transformer2DModel.from_single_file( "https://huggingface.co/stabilityai/...
)# 从 watermark 模块导入水印对象from.watermarkimportIFWatermarker# 如果不进行类型检查且没有慢速导入标志else:# 导入 sys 模块importsys# 将当前模块替换为懒加载模块sys.modules[__name__] = _LazyModule( __name__,# 模块名称globals()["__file__"],# 当前文件路径_import_structure,# 导入结构module_...
使用single-file 方法加载 SD3.5 的 Transformer 模型 Stable Diffusion 3.5 的 transformer 模型还可以使用 Stability AI 发布的原生参数文件来进行初始化 。 这里需要使用 from_single_file 方法: import torch from diffusers import SD3Transformer2DModel, StableDiffusion3Pipeline transformer = SD3Transformer2DModel....
fromdiffusersimportBitsAndBytesConfig,SD3Transformer2DModelimporttorch model_id="stabilityai/stable-diffusion-3.5-large"nf4_config=BitsAndBytesConfig(load_in_4bit=True,bnb_4bit_quant_type="nf4",bnb_4bit_compute_dtype=torch.bfloat16)model_nf4=SD3Transformer2DModel.from_pretrained(model_id,subfolder=...
ControlNet from_single_file is broken when used with a checkpoint that has already been converted: import torch from diffusers import ControlNetModel from huggingface_hub import hf_hub_download local_path = hf_hub_download(repo_id='lllyasviel/sd_control_collection', filename='diffusers_xl_canny...
Describe the bug controlnet loader from_single_file was originally added via #4084 and method ControlNet.from_single_file() works for non-converted controlnets. but for controlnets in safetensors format that contain already converted sta...
from ppdiffusers import StableDiffusionXLPipeline import paddle import uuid pipe = StableDiffusionXLPipeline.from_single_file( "model/XL_model/juggernautXL_v9Rundiffusionphoto2.safetensors", config="config/stable-diffusion-xl-base-1.0", variant="fp16", num_inference_steps=20, paddle_dtype=paddle....