What is the most memory-efficient way to generate images using Diffusers on limited GPUs (<= 4GB VRAM)?

[JohnnyJee]

Discussions!

[nguyenhoanghai1605]

You are creating images with limited VRAM (≤ 4GB), here is what you can do to reduce memory usage in Diffuser:

1. Enable memory-efficient attention:

pipe.enable_xformers_memory_efficient_attention()

2. Use FP16 precision with CUDA:
from diffusers import StableDiffusionPipeline
pipe = StableDiffusionPipeline.from_pretrained("runwayml/stable-diffusion-v1-5", torch_dtype=torch.float16)
pipe.to("cuda")

3. Disable safety checker (optional to save memory):
pipe.safety_checker = lambda images, **kwargs: (images, False)

4. Use pipe.enable_model_cpu_offload() if you're working with low VRAM:
pipe.enable_model_cpu_offload()

[nitinmukesh]

Which model do you want to use and which GPU?