[entrep]

Thanks for these instructions.

Unfortunately I'm getting this error message (Win11, 3080 10GB):

> RuntimeError: CUDA out of memory. Tried to allocate 3.00 GiB (GPU 0; 10.00 GiB total capacity; 5.62 GiB already allocated; 1.80 GiB free; 5.74 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_CON

Edit:

>>> from GPUtil import showUtilization as gpu_usage

>>> gpu_usage()

| ID | GPU | MEM |

------------------

| 0 | 1% | 6% |

Edit 2:

Got this optimized fork to work: https://github.com/basujindal/stable-diffusion

[orpheansodality]

I also have a 10g card and saw the same thing - to get it working I had to pass in "--n_samples 1" to the command, which limits the number of generated images to 2 in any given run. This has been working fine for me