Closed Dolyfin closed 3 months ago
Hi @Dolyfin Apologies for my very late reply. I was so deep in getting v2 out that I didnt break away from dealing with code and issues to get it out.
Ive yet to test out this PR Ive been sent here https://github.com/erew123/alltalk_tts/pull/242 but that may resolve some of the issues with VRAM. Though Ill take on board your suggestion for an explanation. Im guessing its on Linux you are having the issue.
Ill make a note of this in the Feature requests so that I dont lose track of it
Thanks
Is your feature request related to a problem? Please describe. Finetuning on RTX 3060 12GB with 20s length. Can only fit into VRAM with 1 Batch size. Using Grad 16 to counteract this and now fitting with 10.9GB VRAM usage.
Describe the solution you'd like Just edit the min value in finetune.py
Additional context I'm just lazy to go edit the values every install/update and would help more people with less VRAM to finetune. Add explanation in 'info - batch size' to turn up grad accumulation if batch size is low for optimal training.