Is it possible to run these notebooks with gpu with low memory (8GB)
In the 1st notebook, pipe.enable_attention_slicing() helped me.
But in the second one (Stable Diffusion Deep Dive.ipynb), I get this error message:
RuntimeError: CUDA out of memory.
Tried to allocate 512.00 MiB (GPU 0; 7.80 GiB total capacity; 6.15 GiB already allocated; 142.06 MiB free; 6.67 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
It looks like it is possible to play with CUDA options, and if anyone already knows how to do it, it will be great!