I installed InvokeAI today on a pc with a GTX 980TI for testing and i did select said option, but it installed versions of torch and torchvision that did not support the old CUDA version of this specific card.
I fixed it by manually going into the developer console and tying:
uv pip uninstall torch torchvision xformers
uv pip install torch==2.5.0 torchvision==0.20.0 xformers --index-url https://download.pytorch.org/whl/cu124
After that invoke works at least for SDXL since i did not test more scenarios.
Works as in 8-9sec per iteration. Uses around all of the 6gb vram without lowvram-toggle and around 4gb with it enabled.
The command was sourced from here https://github.com/llmlaba/llmlaba.github.io/blob/main/_articles/cuda-pytorch-compatibility.md if anyone reading this has another gpu that falls into this issue and here https://developer.nvidia.com/cuda/gpus/legacy is nvidias list for which gpu does which cuda version.
I installed InvokeAI today on a pc with a GTX 980TI for testing and i did select said option, but it installed versions of torch and torchvision that did not support the old CUDA version of this specific card.
I fixed it by manually going into the developer console and tying:
uv pip uninstall torch torchvision xformersuv pip install torch==2.5.0 torchvision==0.20.0 xformers --index-url https://download.pytorch.org/whl/cu124After that invoke works at least for SDXL since i did not test more scenarios.
Works as in 8-9sec per iteration. Uses around all of the 6gb vram without lowvram-toggle and around 4gb with it enabled.
The command was sourced from here https://github.com/llmlaba/llmlaba.github.io/blob/main/_articles/cuda-pytorch-compatibility.md if anyone reading this has another gpu that falls into this issue and here https://developer.nvidia.com/cuda/gpus/legacy is nvidias list for which gpu does which cuda version.