Comments (3)
I got the same message. Could you fix this?
from thechosenone.
@paratechnical @JahnKhan I've had some success using the following https://huggingface.co/docs/diffusers/optimization/memory#memoryefficient-attention, the pipeline is instantiated in the load_trained_pipeline
function, where you should be able to try reduce the memory usage as per the hugging face article.
Because I was still low on VRAM I went to the pipe.enable_sequential_cpu_offload()
option, which is much slower but working :). I haven't tried model offloading yet, but might be something to try to keep some speed.
from thechosenone.
if model_path is not None:
# TODO: long warning for lora
pipe = DiffusionPipeline.from_pretrained(model_path, torch_dtype=torch.float16)
if load_lora:
pipe.load_lora_weights(lora_path)
else:
pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-base-1.0")
pipe.to("cuda")
pipe.enable_xformers_memory_efficient_attention()
pipe.enable_sequential_cpu_offload()
tried it like this and I have the same problem
What kind of GPU configuration are you using?
from thechosenone.
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from thechosenone.