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If you are having this problem, is a hardware bug, you can use the float32 option as a work around, but it will require more vram
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thanks for the answer yes I enabled the float32 option and got this error RuntimeError: CUDA out of memory. Tried to allocate 114.00 MiB (GPU 0; 4.00 GiB total capacity; 2.99 GiB already allocated; 0 bytes free; 3.35 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
my graphics card is gtx 1650 super