dlseed / so-vits-svc Goto Github PK

I am a music instructor and I would love to introduce this lovely AI software to our students to try out.

Here in my school we have several Windows 7 Pro 64-bit computers in our classrooms, running on Nvidia GeForce GTX 660M GPU. According to Nvidia, the highest version of graphic driver we can install is 425.31, and the highest CUDA Toolkit we can install would be 10.1.

According to pytorch dot org, with CUDA version 10.1, the highest torch we can install would be:
“torch-1.8.1+cu101-cp39-cp39-win_amd64.whl”.

Here, “cu101” in the file name, is referring to CUDA 10.1.

Any torch version higher than 1.8.1, will have a higher “cu” number attached in the whl file name, such as:
“torch-1.10.0+cu102-cp36-cp36m-win_amd64.whl”, or
“torch-1.13.0+cu116-cp310-cp310-win_amd64.whl”, etc.

In other words, our school can not install any torch higher than version 1.8.1.

In the non-fork so-vits-svc-4.0 program folder, there is a file called “requirements.txt”. We opened that file, and can see it says “torch==1.13.1”. Can we assume torch version 1.13.1 is the lowest minimum requirement for so-vits-svc program to run?

Does it mean we can not install your amazing software on our school’s computers, because our Nvidia GPU are too old, and can’t reach your required pytorch 1.13.1 version? Or maybe it doesn’t matter, a lower pytorch 1.8.1 version can still run?

Too bad! My colleagues have already trained several G_43200.pth models on their home computers, and they can just simply copy these models to our school’s computers and start the voice inference right away. We don’t need to train on the classroom’s computers, we just need to infer on existing models, to demonstrate to our students. Inferring takes an awful lot less of GPU powers to do.

Has anyone tested this program on CUDA 10.1?

Please let me know. So, should I give up? Is it a death penalty for our students to see this?