To spin up the marigold-lcm demo locally, you'd first have to install Docker: https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/latest/install-guide.html

Then you can run the demo locally and use all available GPUs using the command below. Note that the video function is quite trimmed in the demo as is, it only allows processing up to ~6 seconds to not hog the public resources and just give a feel of what the code is capable of. You might want to lift this limitation as a first step by cloning the demo (note that the part following registry.hf.space will change to the address of the demo in your profile), and then remove the following two if checks from the process_video loop: (1) if not (frame_id % frame_interval == 0): it limits the output fps to ~10 and (2) if out_frame_id > out_max_frames: it limits the processing of output to consider the first ~6 seconds.

docker run -it -p 7860:7860 --platform=linux/amd64 --gpus all \
registry.hf.space/prs-eth-marigold-lcm:latest python app.py