well im hoping mrq can make it for simple to follow.. cuz i dont even get it
so in a sense.. what benefit could you get out of it? in inference speed? or quality?
not gonna lie, i dont really understand the graphs... what is good and what is bad lol?
idk what i did to do this tbh... but i trained a model, i switched to the model in settings, and then in generating tab i selected the voice of the 5min audio i had. i then clicked recompute voice…
im having the same issue on paperspace not sure how to fix it.
ill try to re-train, but now due to the latest notebook updates, i cant run the google colab version on paperspace to do my ffmpg work-around... i dont why it wont install ffmpg with the…
Im not sure what extra info i need to add? my dataset is literally 5min long, it creates 70 voice and text dataset for that after validation. i train it to 500 epochs, that save every 50 at a…
honestly it sounded decent tbh.... not perfect, it was only 5min recording of me just reading random stuff from something.
ive managed to get it to work on paperspace, in a way you have to first run the google colab notebook, because that somehow manages to fix the ffmpg error for preparing data, run that webui..…
i didnt save models 150 sadly so i never knew how good or bad it was.
But now on the re-runs:
tbh finetuned model 32 wasnt even that bad it was not perfect but decent.... but not sure why…