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For the people that run this locally, how long does it take to generate a video and what gpu are you using?
For the people that run this locally, how long does it take to generate a video and what gpu are you using?
Also, i only have a rtx 3060 with 12gb of vram, any way i can run it?
This demo requires about 16GB CPU RAM and 16GB GPU RAM.
It takes about 20 seconds to generate a video on the A100 GPU.
This demo requires about 16GB CPU RAM and 16GB GPU RAM.
It takes about 20 seconds to generate a video on the A100 GPU.
20 seconds is very short, shouldnt take too long on a rtx 3090 i suppose
I'm using a Xiaomi phone lol
I'm using a Xiaomi phone lol
locally?
I'm using a Xiaomi phone lol
locally?
That's a joke
Is it not possible to allow a way for the user to tweak the settings lower in order for it to work with a RTX 2060 Super (6GB)? Theoretically, later I would be able to enhance the low-res video using an AI Video Enhancer program such as Topaz video AI. I used to do the same process to be able to generate images in Stable Diffusion with my low-key video-card.
Anyway, even if what I'm thinking is possible, it seems I need to plan myself to buy a better video card, hehehehe...
If you download it locally, can you increase the frames/total length of video?
I am also using a RTX 3060 12GB. Res. 256x256 takes ~23 sec.
If you download it locally, can you increase the frames/total length of video?
yes, but there are several things you'll need to do:
- download the pruned weights and config file and replace the ones used here (https://huggingface.co/kabachuha/modelscope-damo-text2video-pruned-weights/tree/main)
- adjust the size of the video output to adjust for what you want
- if you want more frames you'll need something smaller than 256x256, say 256x192
- you'll need to adjust the fps
I installed the Modelscope extension in Automatic1111 and then replaced the weights and config files from ^ and was able to get 10s at 8fps 256x128 on a 3060 running on a laptop
I keep getting this error:
RuntimeError: TextToVideoSynthesisPipeline: TextToVideoSynthesis: Attempting to deserialize object on a CUDA device but torch.cuda.is_available() is False. If you are running on a CPU-only machine, please use torch.load with map_location=torch.device('cpu') to map your storages to the CPU.