Kanye West

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Kanye West

ArtistRVC v2English
2 years ago
👀

47k

👍

177

🪄

12k

Description

I have a patreon where you can support my RVC stuff (colabs, guides, models, etc) and also get access to direct tech support on how to use the models Link to the 40khz version (I think I prefer this): Link to the 48khz version: Retrained with a better, crisper dataset courtesy of and trimmed down by hand, cleaned up, and further polished by me to the best 20 minutes of data that there is. I sent the dataset to nano so it could be trained by him on his fast AF GPU. Enjoy!

Comments

yeezybeezydeezy user image
yeezybeezydeezy
2 years ago

i hope you die

yeezybeezydeezy user image
yeezybeezydeezy
2 years ago

there goes mine lmao

yraziel user image
yraziel
2 years ago

As a music producer I was surprised that 40hz is the default. While I’m writing this my first 48khz model is training!

thataiguy user image
thataiguy
2 years ago

We just got 48k training, so that's why 40k is the default.

yraziel user image
yraziel
2 years ago

Oh didn’t know that

thataiguy user image
thataiguy
2 years ago

Makes it even worse that RVC v3 is in development just as we get RVC v2 48k.

yraziel user image
yraziel
2 years ago

As long as we have RVC im happy 😂

thataiguy user image
thataiguy
2 years ago

Honestly, 48k has been very good in my experience.

thataiguy user image
thataiguy
2 years ago

If a model is iffy, its usually due to Mango Crepe or how iffy the dataset is.

leejhay user image
leejhay
2 years ago

<@729920568207343688> did you resample your dataset in 40k if you want to train it on 40k model?

leejhay user image
leejhay
2 years ago

i did it on my own model and it sounds flawless and clean

leejhay user image
leejhay
2 years ago

in which procedure? preprocessing? feature extraction? my previous models sound robotic when my dataset was 44.1k sp and trained on 40k

leejhay user image
leejhay
2 years ago

i tried 48k and, i think it's experimental, it sounds robotic on high pitched notes using mangio-crepe method

leejhay user image
leejhay
2 years ago

maybe pre-trained model that i used on v2

leejhay user image
leejhay
2 years ago

it hasn't but can handle very well on 40k model that trained with 40k sr dataset

leejhay user image
leejhay
2 years ago

i will look at it on my next training

yeezybeezydeezy user image
yeezybeezydeezy
2 years ago

cokc

leejhay user image
leejhay
2 years ago

yeah, the more dataset you have fed in, the more features it learned from it

leejhay user image
leejhay
2 years ago

my 10-minute dataset can also make my model sound in a reasonable way as long as it's clean and less noisy

leejhay user image
leejhay
2 years ago

i hope that too

leejhay user image
leejhay
2 years ago

yeah i have my 48k dataset ready for that just in case 😅

litsa_the_dancer user image
litsa_the_dancer
2 years ago

sowwy 🥺🥺

leejhay user image
leejhay
2 years ago

oh i didn't know that. thanks for info

yeezybeezydeezy user image
yeezybeezydeezy
2 years ago

thats realtime btw^

yeezybeezydeezy user image
yeezybeezydeezy
2 years ago

yes

yeezybeezydeezy user image
yeezybeezydeezy
2 years ago

i was bored

insect14 user image
insect14
2 years ago

kanye singing 20 min by lil uzi vert

litsa_the_dancer user image
litsa_the_dancer
2 years ago

some songs should not be touched

insect14 user image
insect14
2 years ago

this is a joke

Alex Andain user image
Alex Andain
11 months ago

Please .I can't get a chorus of people

MImouto(๑˃̵ᴗ˂̵) user image
MImouto(๑˃̵ᴗ˂̵)
11 months ago

I like this, great job,dude:3

Eva user image
Eva
10 months ago

Cool voice model👍🏻❤️

Blodlul user image
Blodlul
10 months ago

Do heaven got a penthouse

Joshua Ly user image
Joshua Ly
10 months ago

the ai refrence is crazy bro

S4MI user image
S4MI
10 months ago

Cool

YE user image
YE
9 months ago

Nitrus please

bubble fart user image
bubble fart
9 months ago

YO KANYA OMG!!!

Hector user image
Hector
5 months ago
€VIL ¥$ user image
€VIL ¥$
3 months ago

Ye, you should use more AI

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Samples

New
Classic
1. Singing
Male
English
2. Singing
Female
English
3. Singing (Dry)
Female
English
4. Singing (High)
Female
English
5. Singing 2
Male
English
6. Singing (Dry)
Male
English
7. Singing (Dry, High)
Male
English

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