I think because its not general topic but very specific for those who are really looking for it land here, also diffusion came only last year so less audience.
TH-cam is stupid… instead of suggesting memes I found on the internet should have suggested this gem much sooner. Thank you so much subscribed + liked seems not enough
hello can you help me with the code i have followed this full video but to run the ipynb notebook i am facing some issue regarding creating virtual environment
Llama2 from scratch was superb. i learned lot of things from that video. thank you very much for doing things from scratch . when we use huggingface i feel guilty of using blackbox models. now i can understand whats going on under the hood
Ohhh, it is so true about feeling guilty. I don't like it too. That is why is watch such videos. I also implemented mini-pytorch from scratch because of that feeling, to fully understand what i am doing.
This is the best video about SD! It would be awesome if you could make a video on how to train the model from scratch on some own data. For sure, normal people can never train this network to perfection, but there are a lot of people out there who have a very specific task for which this network could be used. I see a lot of potential for scientific use cases if there was guidance on how to implement it!
Thank you! Please make sure to like, subscribe and share the video with friends and colleagues. That's the best way to help me and the others trying to learn deep learning models.
Thank you! I've been looking and looking and no good tutorial exists on how to do diffusion from scratch. Everyone only seems to be interested in using premade models. Your video is super helpful
Wow, I'm a master's student in China. I learned a lot about stable diffusion from this video. Thank you for sharing, I hope to see more knowledge sharing about stable diffusion.
I am an ai, and I love following updates on social media platforms and TH-cam, and I love your videos very much. I learn the English language and some programming terms from them, and update my information. You and people like you help me very much. Thank you.
@ita Yes, for the most part. I would appreciate if he would include some details on how to modify the program to use safetensors instead of CKPT files since I believe CKPT files are kind of outdated.
You are the best lecturer I've ever seen, very detailed and clearly, I'd love to see more vedios from you! If possible,I would like to konw more about the stable diffusion, such as controlNet, or other novel tools. Finally, thank you once more!
It is a pity, I did not discover your youtube channel earlier. Great presentation. It is only when you go through all the details, that you can fully understand these AI algorithms.
Brambilla Jamil, sei il numero uno! Sto consigliando a tutte le persone a cui faccio mentoring (miei intern) i tuoi video. Meriti 100 volte i tuoi iscritti!
Great tutorial dude ! At first it was a bit hard to get used to your coding style but it was an awesome journey because I learned a lot and I am currently working on my on Stable Diffusion model with my own vision for the models ,
Great work! Thanks for putting this all together. Very easy to follow and simple explanations of complex ideas! It helps a lot to code along the explanation
"oh let me just finish this attention layer and then i will give my cat attention. why do everyone need my attention?" thank you for another banger umar
Awesome video with great information. This video can leverage AI coding skills, along with an understanding of convolutional neural networks, UNet architecture, and Autoencoder, besides the entire stable diffusion architecture.
Amazing video. You explained it so clear. Thank you for putting effort into this lecture. If possible, would you please create a lecture about YOLO codes.
@@李洋-i4j Of course you can change the CLIP model to another CLIP model trained for the Chinese language, but you will also need to fine tune the Unet model so it gets used to the Chinese language. The reason is that the Unet does not recognize embeddings produced by other CLIP models.
Hello Umar, you always produce the most concise and clear content ever! I was wondering if you are planning to do any video on the stable diffusion 3 since the paper is out? It would be really great if you could help explain how the flow matching helps or changes regular diffusion models! Thank you again for your content and work. 非常感谢！
Your video is amazing........................ can you please upload the videos periodically on the latest Machine learning papers as well please its a request i have a dream of reading the ML papers and can implement it by my own.... and you are the one who can me as million of others students in achieving so...............
that was really lovely and great from you thanks alot i would be more happy if you showed us how to fine tune your model that will make the whole video simply perfect
Thank you Umar for the great work. I love your style of teaching which helps imagine concepts and connect dots in our head.🙂 If possible please make videos on basics of probability, distributions and related statistics. It would be really helpful to learn these concepts in your style.
the constant you scale by the x come from averaging over a bunch of examples generated by the vae, in order to ensure they have unit variance with the variance taken over all dimensions simultaneously, scale_factor = 1 / std(z)
As usual, code and PDF slides available on GitHub: github.com/hkproj/pytorch-stable-diffusion PS: no cats were harmed during the making of this video. 奥利奥 (pronounced "Aoliao", which is the Chinese name for the Oreo biscuits) wanted to be part of the video as well, that's why you'll hear his miao-ing from time to time. Right after recording, I played with him for a while to compensate the lack of attention. Hope he won't distract you too much while listening.
Sir your videos are awesome, and I got to learn a lot. We want more videos like this. I am open to (really wanna ) help you for making this type of educative content for free, so we can contribute to community.
@@PurpleSmite Hi! Thank you for your support. The best way to help is to share the videos with your friends, school mates, university and coworkers. My schedule is quite tight and irregular as of now, but I'll let you know if there's something we can work on together. Let's connect on LinkedIn!
Hi, i really like your work. I wanna ask that if i want to generate multi coherent image like a sequence of images out of the code there, what could i add to the code to make it possible?
Dacci il tuo IBAN così possiamo ringraziarti nel modo più adeguato per questo bellissimo regalo! 😂 Best tutorial I followed since I study DMs (one year). Thank you so much!
Ciao Barbara, ti ringrazio molto. Il modo migliore per supportarmi è condividere il video sui social media, mi sarebbe di grande aiuto. Grazie mille e buon weekend!
only 4.8k views feels criminal for how helpful this video is... by far the best stable diffusion video on the internet
I think because its not general topic but very specific for those who are really looking for it land here, also diffusion came only last year so less audience.
TH-cam is stupid… instead of suggesting memes I found on the internet should have suggested this gem much sooner. Thank you so much subscribed + liked seems not enough
Like videos like this and watch them fully more often and you'll get them. Create another account for memes.
@@Katatonya i do but steal youtube push for some stupid trending videos.
hello can you help me with the code i have followed this full video but to run the ipynb notebook i am facing some issue regarding creating virtual environment
can you help me @Pouya..
Llama2 from scratch was superb. i learned lot of things from that video. thank you very much for doing things from scratch . when we use huggingface i feel guilty of using blackbox models. now i can understand whats going on under the hood
Be sure guys from HF are glad you like their API, chin up!
Ohhh, it is so true about feeling guilty. I don't like it too. That is why is watch such videos. I also implemented mini-pytorch from scratch because of that feeling, to fully understand what i am doing.
This is the best explanation of latent diffusion models I've seen
what the fuck this is like the best explanation on this planet. I have some experience in this but his explanation was so crystal clear
Amazing job my friend! I just got a job in ShenZhen China by learing it! Thank u so much mate. I hope u and ur family living a great in China :)
That's great! Let's connect on LinkedIn or WeChat
This is the best video about SD! It would be awesome if you could make a video on how to train the model from scratch on some own data. For sure, normal people can never train this network to perfection, but there are a lot of people out there who have a very specific task for which this network could be used. I see a lot of potential for scientific use cases if there was guidance on how to implement it!
exactly my thought
i hope he does post a video on training the model from scratch
Your code is so detailed and it runs on my enviorment just fine. Great job!!!👏
Thank you! Please make sure to like, subscribe and share the video with friends and colleagues. That's the best way to help me and the others trying to learn deep learning models.
Thank you! I've been looking and looking and no good tutorial exists on how to do diffusion from scratch. Everyone only seems to be interested in using premade models. Your video is super helpful
Wow, I'm a master's student in China. I learned a lot about stable diffusion from this video. Thank you for sharing, I hope to see more knowledge sharing about stable diffusion.
Thank you so much. Just can't express in word the value you have created here.
I am an ai, and I love following updates on social media platforms and TH-cam, and I love your videos very much. I learn the English language and some programming terms from them, and update my information. You and people like you help me very much. Thank you.
Thank you so much for this! Literally no other youtube video provides as much value on this topic as you have.
where you able to run it with no issues ?
@ita Yes, for the most part. I would appreciate if he would include some details on how to modify the program to use safetensors instead of CKPT files since I believe CKPT files are kind of outdated.
@@dinonuggieproductions would you be down to talk about this on discord ?
Appreciating your effort in breaking down the concept so well!!This is the best insightful explanation of stable diffusion I have came across...
I just discovered a great, wonderful, amazing, fantastic, gem channel 🎉🎉🎉
You are the best lecturer I've ever seen, very detailed and clearly, I'd love to see more vedios from you! If possible,I would like to konw more about the stable diffusion, such as controlNet, or other novel tools. Finally, thank you once more!
Amazing work!!
I've been looking for tutorials such detailed and from scratch. 谢谢你。
Omg finally a Chinese here, 你习惯他的口音吗，我听着真的好折磨啊，但是他讲的内容又不错，我真的是😅
It is a pity, I did not discover your youtube channel earlier. Great presentation. It is only when you go through all the details, that you can fully understand these AI algorithms.
Wow. This video is pure gold. Very nicely explained and I'm still only 30 mintues into it!
Brambilla Jamil, sei il numero uno! Sto consigliando a tutte le persone a cui faccio mentoring (miei intern) i tuoi video. Meriti 100 volte i tuoi iscritti!
Great work! As a graduate student taking AI courses, this is really, REALLY helpful. Keep on going 💙
Absolutely first-rate presentation. So impressive.
太强了，简直是最好的diffusion视频
确实，不过意大利口音真的有点挨不住啊
Great tutorial dude ! At first it was a bit hard to get used to your coding style but it was an awesome journey because I learned a lot and I am currently working on my on Stable Diffusion model with my own vision for the models ,
This legend deserves an award from government
Honestly the best video I've seen on stable diffusion! Thanks man!
Outstanding, so well structured and explained!
woahhhh!!! BESTTTTT. watching your video for the first time and I am hooked! Amazing way to explain.
What a great video. Thank you from Japan.
Best explanation of latent diffusion model.
That's what I was looking for, thanks!
thank you so much for the detailed and practical videos! I will watch it again and again!
Thanks so much for for taking time to make this, helps me a lot!❤ Italy accent is a little hard to follow though 😂
Great work! Thanks for putting this all together. Very easy to follow and simple explanations of complex ideas! It helps a lot to code along the explanation
Your explanation and documents are wonderful! They are clear and helpful! Thank you for your hard work :)
Thank you so much! And your Chinese is really good! Your cat is also cute and its voice doesn't bother me but comfort me!
谢谢你！
This is great! Going through the CLIP part right now ^^
An extremely detailed video about diffusion. I have learned a lot. Thank you ❤❤❤
Thanks for your contribution. Can you make a tutorial on how to train the diffusion model on a custom dataset?
the most powerfull deep learning videos in the world are on this channel
absolutely awesome, this is the best explanation of SD thank you so much !!
This is so bonkers. Cheers Mate, you've saved me sometime. Thanks.
I love your videos. They are very informative. Thank you so much for explaining these complex concepts so clearly! Gem channel indeed!
instant subscribe
Thank you a lot for this amazing video. It helped me understand better diffusion models for my masters.
Great bro, really helpful to understand in detail, thanks for the efforts,
Really great video for understanding stable diffusion in detail. Thanks a lot for your contribution
Thanks so much! I've just started learning diffusion models and this video is such an eye-opener!
"oh let me just finish this attention layer and then i will give my cat attention. why do everyone need my attention?" thank you for another banger umar
Dude, you are a bless! Keep it coming and thanks!
Hey bro thank you for existing.
Very grateful to you.
Thank you so much! the best stable diffusion video I found!!!
man man, thanks for all of the amazing videos! I appreciate the work you put in here!
bro thankyou so much i complete the video in 1 sitting wonderful bro
Always a fan of your video. Your explanation is very informative and helpful for beginner data scientist. Thank you very much.
It's the best explaination ever!!!! Thank you!
不客气🤓
Amazing video, you are a blessing Umar! I was wondering if you would ever revisit to work on the in-painting. So curious how you would implement it.
I appreciate your work, thank you for your hard work and videos
By far best explanation ❤
Awesome video with great information. This video can leverage AI coding skills, along with an understanding of convolutional neural networks, UNet architecture, and Autoencoder, besides the entire stable diffusion architecture.
Awesome, This is the best explanation!!!
Thank you! Please keep doing videos like this! I subscribed, liked and shared!
Amazing video. You explained it so clear. Thank you for putting effort into this lecture. If possible, would you please create a lecture about YOLO codes.
Awesome. Thanks for creating the video .
小乌老师好棒！超级好的教程，关注了！
我们在领英联系一下，我想邀请你加入我的AI微信小群
Thanks for your contribution. Hope that one day you will also make a deep dive into ControlNet code etc.
Awesome Explanation, thanks for such tutorial
中秋节快乐！又一部伟大的作品，内容丰富，受益良多~
谢谢你, 祝你和家人国庆节快乐！
hi 我突然想到一个问题：CLIP模型和SD模型必须完全对应吗？如果换成一个用中文语料训练的CLIP模型，可以和SD-v1.5一起使用吗？@@umarjamilai
@@李洋-i4j Of course you can change the CLIP model to another CLIP model trained for the Chinese language, but you will also need to fine tune the Unet model so it gets used to the Chinese language. The reason is that the Unet does not recognize embeddings produced by other CLIP models.
almost karpathy level explanations, thank you!
Umar, thank you for great explanation of topic
This is one of the best video , Thank you
Amazing video, thanks for showing the low level details
This is amazing video!! Great job!!!
Hello Umar, you always produce the most concise and clear content ever! I was wondering if you are planning to do any video on the stable diffusion 3 since the paper is out? It would be really great if you could help explain how the flow matching helps or changes regular diffusion models! Thank you again for your content and work. 非常感谢！
Coming from a reddit post. I don't know how we are suppose to thank you for all this.
Subscribe and share it with the world... best way to thank me ;-)
Great work! This is the place I learned AI. Thanks a lot!
Love from HK. Thank you sooooooo much! 谢谢！
也祝你在苏州生活一切顺利！
Amazing!!! Please do more on computer vision.
Thanks Man for this amazing video.❤❤❤❤
Thank you for the wonderful video. Can you also post how to train the model with a sample dataset?
Your video is amazing........................ can you please upload the videos periodically on the latest Machine learning papers as well please its a request i have a dream of reading the ML papers and can implement it by my own.... and you are the one who can me as million of others students in achieving so...............
that was really lovely and great from you thanks alot i would be more happy if you showed us how to fine tune your model that will make the whole video simply perfect
thanks youuuu, I feel really good after this one
Dame TH-cam, why is this wonderful tutorial so little view??
only with you I understood how it works and how it can be implemented)
Mate, you're golden
Criminally underrated.
Thank you Umar for the great work.
I love your style of teaching which helps imagine concepts and connect dots in our head.🙂
If possible please make videos on basics of probability, distributions and related statistics. It would be really helpful to learn these concepts in your style.
the constant you scale by the x come from averaging over a bunch of examples generated by the vae, in order to ensure they have unit variance with the variance taken over all dimensions simultaneously, scale_factor = 1 / std(z)
As usual, code and PDF slides available on GitHub: github.com/hkproj/pytorch-stable-diffusion
PS: no cats were harmed during the making of this video. 奥利奥 (pronounced "Aoliao", which is the Chinese name for the Oreo biscuits) wanted to be part of the video as well, that's why you'll hear his miao-ing from time to time. Right after recording, I played with him for a while to compensate the lack of attention.
Hope he won't distract you too much while listening.
Sir your videos are awesome, and I got to learn a lot. We want more videos like this. I am open to (really wanna ) help you for making this type of educative content for free, so we can contribute to community.
@@PurpleSmite Hi! Thank you for your support. The best way to help is to share the videos with your friends, school mates, university and coworkers. My schedule is quite tight and irregular as of now, but I'll let you know if there's something we can work on together. Let's connect on LinkedIn!
@@umarjamilai Sure sir, I have sent you on LinkedIn Shreyas Waghmode
Hi, i really like your work. I wanna ask that if i want to generate multi coherent image like a sequence of images out of the code there, what could i add to the code to make it possible?
Your are great sir I want your help can you give me linkdin id
Really appreciated, very informative.
Thanks Dear For helping Us , you Video's are very helpful
excellent video, full of information
woooooooooooooo stable diffusion from scratch love you bro
Great videos. Would love to see implementations of score-based models, ode/sde frameworks and different samplers - if you get a chance.
That's my next step. Stay tuned!
This is mind blowing.
谢谢你，总算清楚sampler和unet之间的关系了
Dacci il tuo IBAN così possiamo ringraziarti nel modo più adeguato per questo bellissimo regalo! 😂
Best tutorial I followed since I study DMs (one year).
Thank you so much!
Ciao Barbara, ti ringrazio molto. Il modo migliore per supportarmi è condividere il video sui social media, mi sarebbe di grande aiuto. Grazie mille e buon weekend!
jesus I have base knowledge of AI and Statistics but you made me understand quite a lot of things thanks to your vid
Mash'Allah! Thank you for the resources!