如何优化显存使用

[ITTWTTI]

torch.cuda.OutOfMemoryError: CUDA out of memory. Tried to allocate 256.00 MiB (GPU 0; 8.00 GiB total capacity; 7.31 GiB already allocated; 0 bytes free; 7.99 GiB allowed; 7.78 GiB reserved in total by PyTorch) If reserved memory is >> allocated memory try setting max_split_size_mb to avoid fragmentation.  See documentation for Memory Management and PYTORCH_CUDA_ALLOC_CONF

如题

CPU：5800H
显卡：3070 loptop 8G
内存：64GB

Image Creator
Model type：sd_xl_turbo_1.0_fp16.safetensors

Drawing tool：freedraw
Stroke width：50
Denoising strength：0.7
Repetition：6

Generate image：
enable auto update
columns：3

[Artiprocher]

1. Lower resolution
2. Smaller animatediff_batch_size (sliding_window_size)
3. Use vram_limit_level=1 in your pipeline

[lonngxiang]

推理怎么优化显存呢，运行也报cuda不足,4090卡 @Artiprocher

from diffsynth import ModelManager, KolorsImagePipeline, download_models
import torch

# Download models
# https://huggingface.co/Kwai-Kolors/Kolors
download_models(["Kolors"])
model_manager = ModelManager(torch_dtype=torch.float16, device="cuda:1",
                             file_path_list=[
                                 "models/kolors/Kolors/text_encoder",
                                 "models/kolors/Kolors/unet/diffusion_pytorch_model.fp16.safetensors",
                                 "models/kolors/Kolors/vae/diffusion_pytorch_model.fp16.safetensors"
                             ])
pipe = KolorsImagePipeline.from_model_manager(model_manager)

prompt = "一只小狗蹦蹦跳跳，周围是姹紫嫣红的鲜花，远处是山脉"
negative_prompt = ""

torch.manual_seed(7)
image = pipe(
    prompt=prompt,
    negative_prompt=negative_prompt,
    num_inference_steps=50,
    cfg_scale=4,
)
image.save(f"image_1024.jpg")