DREAMBOOTH Free For Everyone! No Installation & Troubleshooting Guide!

Key Takeaways

hello humans my name is scared you're a overlord and if you remember correctly in my previous video I taught you how to train stable diffusion with your own images using dreambooth but unfortunately the notebook updated again so technically this video is already outdated but no worries because that the overlord is here to help so in this video not only I will try to solve the most common errors I saw when trying to run dreambooth with rumpled Advanced AI but I will also give you tips and tricks on how you can make your final images look better and finally I will also show you how you can use Dreamboat for free using three different Google column docs and how you can use that finished diffuser model on your own computer are you ready let's go but before we begin just a quick announcement today I officially launched my patreon page so if you want to support my work and my mission and increase your social status from Mere mortal humans to patreon supporters the link will be in the description down below thank you so much in advance for your help alright let's begin first common error Cuda out of memory well this one is a real head scratcher because technically this error should not happen uh because well you only need 24 gigabytes of vram to be able to run this notebook but apparently this area can be solved by increasing the amount of space that you have on your container pod so here for example I have 20 and 20 for containerdesk and volume disk so I highly recommend changing the container disk and volume disk to both 60 gigabytes so your total disk volume will be 120 gigabytes also be careful because something that I noticed is that when you select your template for example if you select the Romper stable diffusion template look what happens on the left right here on the selected it reverts back to the 2020 so this is also a mistake that I almost made be careful that when you choose a template this somehow just revert back to 2020 so again don't forget to change it back to 60 60 and then press on continue also another thing just a little tips from you um there is absolutely no use in choosing multiple gpus this is absolutely useless all right do not like waste your money on this just choose one GPU with at least 24 gigabytes of vram all right so one RTX a 5000 is not the same as for example two RTX A4000 this is not the same what really matters is one GPU having at least 24 gigabytes of vram so if you have for example 6 gpus of 4 gigabytes of vram each that's not going to be the same as one GPU with 24 gigabytes of vram and increasing the amount of gpus that you rent will not decrease the amount of training time that you are gonna need to train your models so don't do this error alright keep your money so common error number two low transfer speed on vast dot AI now this is something that I saw multiple people complaining about and my solution is actually very simple well first of all just make sure that here the uploaded download speed are pretty high when you select your GPU to begin with but also when you click on edit image and config and you select pytorch you want to select this little box right here that says jupyter direct https so if these two boxes checked and then you can click on Save and this will greatly increase the amount of upload and download speed that you get on vast.ai and here again don't forget to maybe increase the amount of disk space that you need so maybe something above 100 gigabytes should be enough and again the same tips applied do not choose multiple gpus only one GPU is enough just just select the cheapest one as you can see here the cheapest one is an on TX 2019 only 29 cents an hour this is what you want comment error number three click to show JavaScript error now this happens when you try to click on login to civil diffusion cell and it gives you this JavaScript error so to solve this error all you have to do is simply refresh the page press on F5 as you can see here if you run the cell again this works correctly now comment error number four name trainer is not defined woof well this one is absolutely insane because I'm saying this because the last night I spent around an hour trying to solve this issue and it's a very difficult error to solve because that's not even an error it's just a bug and unfortunately there's not an easy way to solve this and the only solution that I found is to basically click on the file click on shutdown to shut down the Jupiter lab notebook then go back into your pod and then click on reset pod and then try to relaunch every single cell again this is a very annoying bug because there is absolutely no reason for it to work and in the end the only way that we managed to solve this and just by restarting the part again and again so I'm really hoping that this bug will be fixed in the future releases of the notebook and as of right now this is a very annoying bug to have but if you have this error just simply try to shut down the notebook and restarting the code again and hope that it works this time around comment error number five name data set is not defined now again this is again another bug this is technically not something that you did wrong and the way to solve this is actually pretty simple all you have to do is just to scroll up until you see the data set equals person ddim or any other data set name that you chose you're gonna select that line copy it and scroll down click on this button right here to a new cell paste it and then run the cell and then you can rerun the training cell again very annoying bug but pretty easy to solve comment error number six training ended after only one iteration now this one is also a super common error right now and the way to solve this is actually pretty easy all you have to do is just click on new window right here click on Terminal this will launch a brand new terminal and here you're gonna copy and type p s a u x and what you want to do right now is basically check the PID of the Python relauncher.py and the python web ui.py now in this example right here the PID for the python will launched on the py is 11 and the PID for the python web UI the py is 26 and what you want to do once you have found these two numbers you're gonna type kill and then the number of the PID in my example it's 11 and then kill for the second number and in my case it's 26 and then press enter and then see simply go back to the cell and rerun it again pretty annoying again but you'll see that I learned from Joe mystery Guitar Man on YouTube whose notebook that we are using right now if you want your images to look better here when you choose the name of your character instead of inputting the name of your character you want to input the name of a famous celebrity that looks like your character and this one basically trick stable diffusion into believing that you want images of a certain personality of a certain celebrity and this will basically generate a bigger variation of images and styles than if you were simply to use a character that stable diffusion as no idea exists and my little trick for this is to use a website called starbyface.com where you can actually upload a picture of yourself or a character that you want to train and then it will basically analyze the face and give the celebrity that it looks the most so for example in my case I would like to train the new renera actress and no please do not spoil me to show I haven't watched the last episode yet but basically you input here the image of the character you want to train in my case it's the new renera and then it shows you all the actresses that looks the most like this actress right here but you want to make sure that when you choose the actress or the actor that looks like the most like your character is that stable the fusion has images of that actress so for example if you choose Leanne Rhymes I'm not sure that stable diffusion has been trained with images of that actress but someone like Mary Kate Olsen for example or or even better Elizabeth Olsen is probably the best choice so if you go through stable diffusion for example you select simple diffusion 1.4 and you write in my case a photo of Elizabeth Olsen and you click on dream you need to make sure that stable diffusion has this actress trained already and as you can see here it's not exactly the best representation of Elizabeth awesome but it's pretty close nonetheless so for this all you have to do just scroll down until you see edit the personal spy file and here you can simply replace like jopanna into in my case in the example then you can copy this line right here paste it here and then run the cell and there you go this is what I get in the end with simply using Elizabeth Olsen but if I put a space right here and then click on generate it gives me this which is almost like a mix between these two characters which is absolutely fantastic and it creates a bigger variation of images than if you're aware to Simply use the name of your character alone now what if you don't want to spend money renting a GPU on runboard or vast Ai and you just want to train your images with dream Booth but you don't have a powerful enough computer to be able to run this locally well you have basically another solution which is called Google collab docs and currently there are three different Google call up docs that you can use right now to train stable diffusion with your own images using dreambooth now unfortunately there is currently a big downside to this because if you use a Google collab docs you do not get a ckpt file in the end here's a little document that I made to explain to you a little bit as of right now you have two choices alright either you use run pod or vast Ai and you pay around 40 cents an hour and you use the job in a notebook to train stable diffusion with your own images with dream booth and in the end of the training you get a ckpt file that you can use on super stable diffusion 2.0 or the automatic quadruple one and everything as well or you can use the Google collabs which works with the diffuser model is free but in the end you do not get a ckpg file and this cannot be used with super stimuli Fusion 2.0 all only with g-risk SD GUI which I'm going to show you a little bit later so as of right now you have three different Google column docs that you can use the official from the hugging phase.com website the Shivam Street Rao which uses only 17.7 gigabytes of vram which is apparently also twice as fast as the one above and again the last one which is called the last van which is a 65 percent of speed increase and uses less than 12 gigabytes of vram which is really super impressive and all the links for these Google collab docs will be in the description down below so basically every single one of these Google color blocks works pretty much the exact same way so to be able to use them you need that again face account and you also need to click on this link right here to be able to accept the terms that you see on the page and then you need to create a hanging face token and for this all you have to do is just click on your profile go to settings on access tokens click on new token select the name for your token choose right and then click on generate token and then you can simply click here to copy token to clipboard and then you'll be able to use this on every single one of these Google column docs basically run every single send one after the other just follow the instructions is actually really really easy really simple it's technically a little bit easier than using the notebook for example but in the end all you get is a bunch of folders and not an skpt file now here's something very interesting if you don't want to train your own model because you don't have time and you just want to use models created by the community you can click on description down below and you arrive on this page on the arganface.com website in the stable diffusion dreambooth library and here click on expand you're gonna have all the models that were trained by the community using the Google collab from the onionface.com website and you can use every single one of these models on your own computer and I'm gonna show you how so for example let's say you want to use this one Scarlet Witch For example which is basically a model trained with the face of a Scarlet Witch and to be able to use this you're gonna come here and click on use in diffusers and here you're gonna select this line right here get clone gonna select it Ctrl C then you're gonna create a new folder you're gonna click here on this folder URL type CMD press enter this will bring the command prompt window then you're gonna paste this line right here and press enter now it's going to take around a minute or two to download all the files that it needs and if you go inside that folder you're gonna see a bunch of files and you're gonna be like okay that's nice and all but how how do I use these files there are kind of useless it's not a ckpt file so I can't use this in super stable diffusion but don't worry here's the little trick to be able to use this all you have to do is click on the link in the description down below and you arrive on this page and you see here it's called stable diffusion jirisk GUI 0.1 and this is what you're gonna use to generate your images with the model that you downloaded from the againface.com website so just scroll down click on download this will download a free gigabyte file simply right click click to extract to stable diffusion jurisk GUI I'm not going to do this because it's already done then you're gonna double click on this folder go into the fusion 16 stable the fusion v14 and then you're gonna select all these files you're gonna press Ctrl C to copy these files you're going to create a new folder right here just in case and you're gonna call it copy and inside you're gonna paste the files that you copied from the previous folder just in case then you're gonna go back you're gonna select the model that you downloaded previously in my case its current which I'm gonna select all these files right here Ctrl C go back into the stable diffusion Juris GUI diffusion 16 stable diffusion v14 and then you're gonna press Ctrl V to paste all the files in this folder and when it asks you yes you want to replace all the files in the destination and once this is done you're gonna go back to the stable the fusion gym risk GUI folder scroll down until you see the stable diffusion gui.exe double click on it and here you see a dialog box where you can input your prompt the output folder the steps the scale the number of samples per prompt your seed and the resolution now in my case since it's scored the twitch I'm gonna have to input Scarlet Wii person and to be able to find this you have to go back into into the page where we downloaded the diffuser model and these are already two arguments that we need to use Scarlet wig is basically the name of the character and person is the data set name that was used to train this concept so to be able to use this when you create new images you need to input both Scarlet Wii in person so in my case it's going to be portrait of scarlet Wii person and then you're gonna put all the other additional arguments and then click on render and once this is done to be able to see the results you're gonna scroll up until you see the folder results double click on it and then you're gonna see all the images that were generated with the new prompt and here's the final result so as I said as of right now there is no way to be able to use the models that were created using a Google call app docs on super stable diffusion 2.0 or any other installation of stable diffusion but soon we might get a converter from diffusers into CK pte files and in that case once we have that converter the Google column docs will become way way more useful because once we have a ckpt file we can use it anywhere we want and there we have it folks right now I really hope that you've played around with dreambooth a little bit because this is really a game changer in the world of stable diffusion and AI generated images I absolutely love it once again this video took me a long time to make so I would greatly appreciate if you've become one of my patreons to help you make these videos in the future with that being said thank you so much for watching don't forget to subscribe and smash the like button for the YouTube algorithm and I'll see you soon bye bye