Install Kohya on Windows and Mac! Quick & Easy

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hello everyone today we are going to have a look together on how to install Koya on your computer locally for who doesn't useful for training a stable diffusion model so this is the main GitHub page it's very quick and straightforward to install it mainly now that they have updated the installation process so let's have a look on how to do it together I'm gonna do it on Windows first and then on Mac so first thing to do is to create a new folder I can call it Koya then you can open your command prompt and then you dive into this folder with the CD command the CD desktop because my folder is in the desktop then if you type dear you see where you are and I have this Koya here so I'm gonna dive into this folder like this Dr Koya and I'm now oh sorry not Dr CD Korea and now I mean the folder I just created in here I want to get clone the URL from the git Hub page so you go in here you copy this you go back into your terminal and you type git clone and you paste the repo URL okay cool done so now if you go back into the folder you just created which is Koya you will see you have this Koya SS which is the folder from the GitHub page and you have plenty of folders and files what you have to do very simple you need to First go into this Koya SS folder so if you click there dir you will see you have this Koya SS so CD underscore assess then leave again and you see all of the files and you need to run this setup but actually before doing that let's have a look if you go into the GitHub page you have installation so you can click on Windows and it actually tells you what you have to do right so you see installing you need to run this setup so you can just copy and paste this into your terminal we did already these two steps so you go here Ctrl V so this setup is going to create the BAM environment for a python and then it's going to install or fully the requirements for Koya so this is the update they made recently which is quite useful so if it's the first time you are running installing Koya on your computer you will want to choose the first one so install Koya so you just press one then you need to install the torch version which can be one or two depending on which version you want to install I'm going to use two and this is going to install different packages into your computer in order to run initialize Koya and actually use it this will take a little bit of time not much okay once this has been done you can decide to install Cuda and N if you if you can so again if you go here it is going to tell you what this is and just to wrap up this is for improving the learning speed for NVIDIA so obviously if you have a Mac you cannot do it and also this is just for the Nvidia alternative for the onwards so it's really up to you if you want to do it I'm telling you this changes a lot because the speed is going to be way faster so in case you want to install it you just need to press three otherwise you can initialize Koya just pressing four okay so once you press 4 for initializing Koya this should be quicker and here you go you have Koya installed if you close Koya you want to initialize this again you don't have obviously to go through all of these process even if you can like you just run the setup file and then you choose four otherwise you can also double click on this GUI bath I can press it now double click on this file and you will see you have the URL here you just need to copy and paste this in your browser like this and here you go so this is for Windows let's have a look now on how to do it on Mac we are going to create a folder we we are gonna name it um we go into the Koya SS and then we copy this URL we open the terminal which it can be the normal terminal like this but I'm going to use Warp then I'm going into the folder I just created CD desktop oh yeah and then I'm going to git clone the URL from the repo I just copied once it's done if you open the Koya folder you just created you will have this Koya underscore SS with all of the files and folders from the GitHub repo then if we go into the Gita page we can follow Destruction for Mac which is honestly it's quite easy to to do as suggested here we need to go into the folder with the terminal and then we need to run this setup file so let's do that together so we dive into this and then here you can see all of the files and we need to run this setup file here set up dot sh is going to install all of the tools we need for running koi on our Mac so it's saying that if this operation takes too long you can run it in verbose mode which is something you can do you just need to run it like that yeah but for me the setup is finished so I'm happy with that it's giving us some warnings as you can see here like torch reports code are not available but this is completely normal so no worries it's just a warning it's normal because we are running a Mac and Mac doesn't support Cuda and then you have other warnings but also in this case no worries because it's just telling you look you require this version instead of the current one but as you can see after this installing the required required package which is in this case accelerate and the same is for the others so once this is done you will have this link you just need to copy the link you paste into your browser and you have Koya so that's it I hope this was useful I showed you how to install Koya on both Windows and Mac and see you at the next video bye
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Channel: Laura Carnevali
Views: 22,943
Rating: undefined out of 5
Keywords: stable diffusion, stable diffusion v2, diffusion, ai art, diffusion model, generative ai, generative art, stability ai, ai artist, nft, install stable diffusion, install stable diffusion on mac, install stable diffusion apple silicon, apple silicon, m1, stable diffusion on m1, stable diffusion with python, stable diffusion hugging face, stable diffusion github, stable diffusion v1.5, stable diffusion tutorial, kohya, train model, kohya ss, install kohya, dreambooth, training sd
Id: tZjlTpTZ8Lc
Channel Id: undefined
Length: 7min 9sec (429 seconds)
Published: Mon Jun 12 2023
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