Expert-Level Tutorials on Stable Diffusion & SDXL: Master Advanced Techniques and Strategies
•
3
Furkan Gözükara
MonsterMMORPG
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AI & ML interests
Check out my youtube page SECourses for Stable Diffusion tutorials. They will help you tremendously in every topic
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posted
an
update
1 day ago
Post
617
How to Use SwarmUI & Stable Diffusion 3 on Cloud Services Kaggle (free), Massed Compute & RunPod : https://youtu.be/XFUZof6Skkw
Tutorial link : https://youtu.be/XFUZof6Skkw
It has manually written captions / subtitles and also video chapters.
If you are a GPU poor this is the video you need
In this video, I demonstrate how to install and use #SwarmUI on cloud services. If you lack a powerful GPU or wish to harness more GPU power, this video is essential. You'll learn how to install and utilize SwarmUI, one of the most powerful Generative AI interfaces, on Massed Compute, RunPod, and Kaggle (which offers free dual T4 GPU access for 30 hours weekly). This tutorial will enable you to use SwarmUI on cloud GPU providers as easily and efficiently as on your local PC. Moreover, I will show how to use Stable Diffusion 3 (#SD3) on cloud. SwarmUI uses #ComfyUI backend.
🔗 The Public Post (no login or account required) Shown In The Video With The Links ➡️ https://www.patreon.com/posts/stableswarmui-3-106135985
🔗 Windows Tutorial for Learn How to Use SwarmUI ➡️ https://youtu.be/HKX8_F1Er_w
🔗 How to download models very fast to Massed Compute, RunPod and Kaggle and how to upload models or files to Hugging Face very fast tutorial ➡️ https://youtu.be/X5WVZ0NMaTg
🔗 SECourses Discord ➡️ https://discord.com/servers/software-engineering-courses-secourses-772774097734074388
🔗 Stable Diffusion GitHub Repo (Please Star, Fork and Watch) ➡️ https://github.com/FurkanGozukara/Stable-Diffusion
Coupon Code for Massed Compute : SECourses
Coupon works on Alt Config RTX A6000 and also RTX A6000 GPUs
Tutorial link : https://youtu.be/XFUZof6Skkw
It has manually written captions / subtitles and also video chapters.
If you are a GPU poor this is the video you need
In this video, I demonstrate how to install and use #SwarmUI on cloud services. If you lack a powerful GPU or wish to harness more GPU power, this video is essential. You'll learn how to install and utilize SwarmUI, one of the most powerful Generative AI interfaces, on Massed Compute, RunPod, and Kaggle (which offers free dual T4 GPU access for 30 hours weekly). This tutorial will enable you to use SwarmUI on cloud GPU providers as easily and efficiently as on your local PC. Moreover, I will show how to use Stable Diffusion 3 (#SD3) on cloud. SwarmUI uses #ComfyUI backend.
🔗 The Public Post (no login or account required) Shown In The Video With The Links ➡️ https://www.patreon.com/posts/stableswarmui-3-106135985
🔗 Windows Tutorial for Learn How to Use SwarmUI ➡️ https://youtu.be/HKX8_F1Er_w
🔗 How to download models very fast to Massed Compute, RunPod and Kaggle and how to upload models or files to Hugging Face very fast tutorial ➡️ https://youtu.be/X5WVZ0NMaTg
🔗 SECourses Discord ➡️ https://discord.com/servers/software-engineering-courses-secourses-772774097734074388
🔗 Stable Diffusion GitHub Repo (Please Star, Fork and Watch) ➡️ https://github.com/FurkanGozukara/Stable-Diffusion
Coupon Code for Massed Compute : SECourses
Coupon works on Alt Config RTX A6000 and also RTX A6000 GPUs
posted
an
update
5 days ago
Post
355
LLaVA 1.6 - 34 billion parameters - loaded as 8-bit precision caption. Uses around 37 GB VRAM on Massed Compute with our installers (31 cents per hour with SECourses coupon). A new tutorial for this will be made hopefully soon.
posted
an
update
9 days ago
Post
6570
Zero to Hero Stable Diffusion 3 Tutorial with Amazing SwarmUI SD Web UI that Utilizes ComfyUI
https://youtu.be/HKX8_F1Er_w
Do not skip any part of this tutorial to master how to use Stable Diffusion 3 (SD3) with the most advanced generative AI open source APP SwarmUI. Automatic1111 SD Web UI or Fooocus are not supporting the #SD3 yet. Therefore, I am starting to make tutorials for SwarmUI as well. #StableSwarmUI is officially developed by the StabilityAI and your mind will be blown after you watch this tutorial and learn its amazing features. StableSwarmUI uses #ComfyUI as the back end thus it has all the good features of ComfyUI and it brings you easy to use features of Automatic1111 #StableDiffusion Web UI with them. I really liked SwarmUI and planning to do more tutorials for it.
🔗 The Public Post (no login or account required) Shown In The Video With The Links ➡️ https://www.patreon.com/posts/stableswarmui-3-106135985
0:00 Introduction to the Stable Diffusion 3 (SD3) and SwarmUI and what is in the tutorial
4:12 Architecture and features of SD3
5:05 What each different model files of Stable Diffusion 3 means
6:26 How to download and install SwarmUI on Windows for SD3 and all other Stable Diffusion models
8:42 What kind of folder path you should use when installing SwarmUI
10:28 If you get installation error how to notice and fix it
11:49 Installation has been completed and now how to start using SwarmUI
12:29 Which settings I change before start using SwarmUI and how to change your theme like dark, white, gray
12:56 How to make SwarmUI save generated images as PNG
13:08 How to find description of each settings and configuration
13:28 How to download SD3 model and start using on Windows
13:38 How to use model downloader utility of SwarmUI
14:17 How to set models folder paths and link your existing models folders in SwarmUI
14:35 Explanation of Root folder path in SwarmUI
14:52 VAE of SD3 do we need to download?
https://youtu.be/HKX8_F1Er_w
Do not skip any part of this tutorial to master how to use Stable Diffusion 3 (SD3) with the most advanced generative AI open source APP SwarmUI. Automatic1111 SD Web UI or Fooocus are not supporting the #SD3 yet. Therefore, I am starting to make tutorials for SwarmUI as well. #StableSwarmUI is officially developed by the StabilityAI and your mind will be blown after you watch this tutorial and learn its amazing features. StableSwarmUI uses #ComfyUI as the back end thus it has all the good features of ComfyUI and it brings you easy to use features of Automatic1111 #StableDiffusion Web UI with them. I really liked SwarmUI and planning to do more tutorials for it.
🔗 The Public Post (no login or account required) Shown In The Video With The Links ➡️ https://www.patreon.com/posts/stableswarmui-3-106135985
0:00 Introduction to the Stable Diffusion 3 (SD3) and SwarmUI and what is in the tutorial
4:12 Architecture and features of SD3
5:05 What each different model files of Stable Diffusion 3 means
6:26 How to download and install SwarmUI on Windows for SD3 and all other Stable Diffusion models
8:42 What kind of folder path you should use when installing SwarmUI
10:28 If you get installation error how to notice and fix it
11:49 Installation has been completed and now how to start using SwarmUI
12:29 Which settings I change before start using SwarmUI and how to change your theme like dark, white, gray
12:56 How to make SwarmUI save generated images as PNG
13:08 How to find description of each settings and configuration
13:28 How to download SD3 model and start using on Windows
13:38 How to use model downloader utility of SwarmUI
14:17 How to set models folder paths and link your existing models folders in SwarmUI
14:35 Explanation of Root folder path in SwarmUI
14:52 VAE of SD3 do we need to download?
posted
an
update
25 days ago
Post
2218
V-Express: 1-Click AI Avatar Talking Heads Video Animation Generator - D-ID Alike - Free Open Source
Full Windows YouTube Tutorial : https://youtu.be/xLqDTVWUSec
Ever wished your static images could talk like magic? Meet V-Express, the groundbreaking open-source and free tool that breathes life into your photos! Whether you have an audio clip or a video, V-Express animates your images to create stunning talking avatars. Just like the acclaimed D-ID Avatar, Wav2Lip, and Avatarify, V-Express turns your still photos into dynamic, speaking personas, but with a twist—it's completely open-source and free to use! With seamless audio integration and the ability to mimic video expressions, V-Express offers an unparalleled experience without any cost or restrictions. Experience the future of digital avatars today—let's dive into how you can get started with V-Express and watch your images come alive!
1-Click V-Express Installers Scripts ⤵️
https://www.patreon.com/posts/105251204
Requirements Step by Step Tutorial ⤵️
https://youtu.be/-NjNy7afOQ0
Official Rope GitHub Repository Free To Install and Use ⤵️
https://github.com/tencent-ailab/V-Express
SECourses Discord Channel to Get Full Support ⤵️
https://discord.com/servers/software-engineering-courses-secourses-772774097734074388
Full Windows YouTube Tutorial : https://youtu.be/xLqDTVWUSec
Ever wished your static images could talk like magic? Meet V-Express, the groundbreaking open-source and free tool that breathes life into your photos! Whether you have an audio clip or a video, V-Express animates your images to create stunning talking avatars. Just like the acclaimed D-ID Avatar, Wav2Lip, and Avatarify, V-Express turns your still photos into dynamic, speaking personas, but with a twist—it's completely open-source and free to use! With seamless audio integration and the ability to mimic video expressions, V-Express offers an unparalleled experience without any cost or restrictions. Experience the future of digital avatars today—let's dive into how you can get started with V-Express and watch your images come alive!
1-Click V-Express Installers Scripts ⤵️
https://www.patreon.com/posts/105251204
Requirements Step by Step Tutorial ⤵️
https://youtu.be/-NjNy7afOQ0
Official Rope GitHub Repository Free To Install and Use ⤵️
https://github.com/tencent-ailab/V-Express
SECourses Discord Channel to Get Full Support ⤵️
https://discord.com/servers/software-engineering-courses-secourses-772774097734074388
replied to
their
post
28 days ago
It is open source you can easily install by following github instructions
posted
an
update
28 days ago
Post
1241
Rope is the newest 1-Click, most easy to use, most advanced open source Deep Fake application. It has been just published few days ago. In below tutorials I show how to use Rope Pearl DeepFake application both on Windows and on a cloud machine (Massed Compute). Rope is way better than Roop, Roop Unleashed and FaceFusion. It supports multi-face Face Swapping and making amazing DeepFake videos so easily with 1-Click. Select video, select faces and generate your DeepFake 4K ultra-HD video.
1-Click Rope Installers Scripts (contains both Windows into an isolated Python VENV and Massed Compute — Cloud — No GPU)⤵️
https://www.patreon.com/posts/most-advanced-1-105123768
Tutorials are made only for educational purposes. On cloud Massed Compute machine, you can run with staggering 20 threads and can FaceSwap entire movies. Fully supports face tracking and multiple face changes.
Mind-Blowing Deepfake Tutorial: Turn Anyone into Your Fav Movie Star! Better than Roop & Face Fusion ⤵️
https://youtu.be/RdWKOUlenaY
Best Deepfake Open Source App ROPE — So Easy To Use Full HD Feceswap DeepFace, No GPU Required Cloud ⤵️
https://youtu.be/HLWLSszHwEc
1-Click Rope Installers Scripts (contains both Windows into an isolated Python VENV and Massed Compute — Cloud — No GPU)⤵️
https://www.patreon.com/posts/most-advanced-1-105123768
Tutorials are made only for educational purposes. On cloud Massed Compute machine, you can run with staggering 20 threads and can FaceSwap entire movies. Fully supports face tracking and multiple face changes.
Mind-Blowing Deepfake Tutorial: Turn Anyone into Your Fav Movie Star! Better than Roop & Face Fusion ⤵️
https://youtu.be/RdWKOUlenaY
Best Deepfake Open Source App ROPE — So Easy To Use Full HD Feceswap DeepFace, No GPU Required Cloud ⤵️
https://youtu.be/HLWLSszHwEc
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- 5 replies
posted
an
update
about 1 month ago
Post
407
The zip file contains installers for Windows, RunPod, Massed Compute and a free Kaggle account notebook
It generates a VENV and install everything inside it. Works with Python 3.10.x - I suggest 3.10.11
Also you need C++ tools and Git. You can follow this tutorial to install all : https://youtu.be/-NjNy7afOQ0
Updated 27 May 2024 : https://www.patreon.com/posts/95759342
21 January 2024 Update
SDXL model upgraded to ip-adapter-faceid-plusv2_sd15
Kaggle Notebook upgraded to V3 and supports SDXL now
First of all I want to thank you so much for this amazing model.
I have spent over 1 week to code the Gradio and prepare the video. I hope you let this thread remain and even add to the Readme file.
After video has been published I even added face embedding caching mechanism. So now it will calculate face embedding vector only 1 time for each image, thus super speed up the image generation.
Instantly Transfer Face By Using IP-Adapter-FaceID: Full Tutorial & GUI For Windows, RunPod & Kaggle : https://youtu.be/rjXsJ24kQQg
chapters are like below
0:00 Introduction to IP-Adapter-FaceID full tutorial
2:19 Requirements to use IP-Adapter-FaceID gradio Web APP
2:45 Where the Hugging Face models are downloaded by default on Windows
3:12 How to change folder path where the Hugging Face models are downloaded and cached
3:39 How to install IP-Adapter-FaceID Gradio Web APP and use on Windows
5:35 How to start the IP-Adapter-FaceID Web UI after the installation
5:46 How to use Stable Diffusion XL (SDXL) models with IP-Adapter-FaceID
5:56 How to select your input face and start generating 0-shot face transferred new amazing images
6:06 What does each option on the Web UI do explanations
It generates a VENV and install everything inside it. Works with Python 3.10.x - I suggest 3.10.11
Also you need C++ tools and Git. You can follow this tutorial to install all : https://youtu.be/-NjNy7afOQ0
Updated 27 May 2024 : https://www.patreon.com/posts/95759342
21 January 2024 Update
SDXL model upgraded to ip-adapter-faceid-plusv2_sd15
Kaggle Notebook upgraded to V3 and supports SDXL now
First of all I want to thank you so much for this amazing model.
I have spent over 1 week to code the Gradio and prepare the video. I hope you let this thread remain and even add to the Readme file.
After video has been published I even added face embedding caching mechanism. So now it will calculate face embedding vector only 1 time for each image, thus super speed up the image generation.
Instantly Transfer Face By Using IP-Adapter-FaceID: Full Tutorial & GUI For Windows, RunPod & Kaggle : https://youtu.be/rjXsJ24kQQg
chapters are like below
0:00 Introduction to IP-Adapter-FaceID full tutorial
2:19 Requirements to use IP-Adapter-FaceID gradio Web APP
2:45 Where the Hugging Face models are downloaded by default on Windows
3:12 How to change folder path where the Hugging Face models are downloaded and cached
3:39 How to install IP-Adapter-FaceID Gradio Web APP and use on Windows
5:35 How to start the IP-Adapter-FaceID Web UI after the installation
5:46 How to use Stable Diffusion XL (SDXL) models with IP-Adapter-FaceID
5:56 How to select your input face and start generating 0-shot face transferred new amazing images
6:06 What does each option on the Web UI do explanations
replied to
their
post
about 1 month ago
It works, @MonsterMMORPG !
https://huggingface.co/spaces/Fabrice-TIERCELIN/SUPIR
SUPIR is now available on HuggingFace 🙂 I have disabled LLaVa because there is still an error with it. I will try to fix it in the future. Add links everywhere!
congrats
replied to
their
post
about 1 month ago
OK so I have created a template space. Of course it's not working itself because it runs on a CPU but people can duplicate it on a GPU. It should work but I can only test the interface. I say that they need 60 GB VRAM. Correct me if it's wrong. I will wait for feedback.
Our apps works with 29gb ram on kaggle
Can't tell others
replied to
their
post
about 1 month ago
@Fabrice-TIERCELIN
we have a working Kaggle notebook
Also we have installers for runpod and massed compute
posted
an
update
about 2 months ago
Post
1535
Stable Cascade Full Tutorial for Windows, Massed Compute, RunPod & Kaggle — Predecessor of SD3 — 1-Click Install Amazing Gradio APP
Stable Cascade is another amazing model for Stability AI
Weights are published
Stable Cascade Full Tutorial for Windows — Predecessor of SD3–1-Click Install Amazing Gradio APP : https://youtu.be/q0cYhalUUsc
Stable Cascade Full Tutorial for Cloud — Predecessor of SD3 — Massed Compute, RunPod & Kaggle : https://youtu.be/PKDeMdEObNo
Stable Cascade is another amazing model for Stability AI
Weights are published
Stable Cascade Full Tutorial for Windows — Predecessor of SD3–1-Click Install Amazing Gradio APP : https://youtu.be/q0cYhalUUsc
Stable Cascade Full Tutorial for Cloud — Predecessor of SD3 — Massed Compute, RunPod & Kaggle : https://youtu.be/PKDeMdEObNo
replied to
their
post
about 2 months ago
sadly i can't for this. I also don't know and this requires good GPU
posted
an
update
about 2 months ago
Post
2637
The IDM-VTON (Improving Diffusion Models for Authentic Virtual Try-on in the Wild) is so powerful that it can even transfer beard or hair as well.
I have prepared installer scripts and full tutorials for Windows (requires min 8 GB VRAM GPU), Massed Compute (I suggest this if you don’t have a strong GPU), RunPod and a free Kaggle account (works perfect as well but slow).
Windows Tutorial : https://youtu.be/m4pcIeAVQD0
Cloud (Massed Compute, RunPod & Kaggle) Tutorial : https://youtu.be/LeHfgq_lAXU
I have prepared installer scripts and full tutorials for Windows (requires min 8 GB VRAM GPU), Massed Compute (I suggest this if you don’t have a strong GPU), RunPod and a free Kaggle account (works perfect as well but slow).
Windows Tutorial : https://youtu.be/m4pcIeAVQD0
Cloud (Massed Compute, RunPod & Kaggle) Tutorial : https://youtu.be/LeHfgq_lAXU
posted
an
update
2 months ago
Post
3279
Complete Guide to SUPIR Enhancing and Upscaling Images Like in Sci-Fi Movies on Your PC : https://youtu.be/OYxVEvDf284
In this video, I explain how to 1 click install and use the most advanced image upscaler / enhancer in the world that is both commercially and open source available. The upscaler that I am going to introduce you is open source #SUPIR and the model is free to use. SUPIR upscaler is many times better than both paid Topaz AI and Magnific AI and you can use this upscaler on your computer for free forever. The difference of SUPIR vs #Topaz and #Magnific is like ages. So in this tutorial you are going to learn everything about how to install, update and use SUPIR upscaler on your personal computer. The video shows Windows but it works perfectly fine on Linux as well.
Scripts Download Link ⤵️
https://www.patreon.com/posts/99176057
Samplers and Text CFG (Text Guidance Scale) Comparison Link ⤵️
https://imgsli.com/MjU2ODQz/2/1
How to install accurate Python, Git and FFmpeg on Windows Tutorial ⤵️
https://youtu.be/-NjNy7afOQ0
Full DreamBooth / Fine-tuning Tutorial ⤵️
https://youtu.be/0t5l6CP9eBg
Scaling Up to Excellence: Practicing Model Scaling for Photo-Realistic Image Restoration In the Wild : https://arxiv.org/abs/2401.13627
Authors introduce SUPIR (Scaling-UP Image Restoration), a groundbreaking image restoration method that harnesses generative prior and the power of model scaling up. Leveraging multi-modal techniques and advanced generative prior, SUPIR marks a significant advance in intelligent and realistic image restoration. As a pivotal catalyst within SUPIR, model scaling dramatically enhances its capabilities and demonstrates new potential for image restoration. Authors collect a dataset comprising 20 million high-resolution, high-quality images for model training, each enriched with descriptive text annotations. SUPIR provides the capability to restore images guided by textual prompts, broadening its application scope and potential
In this video, I explain how to 1 click install and use the most advanced image upscaler / enhancer in the world that is both commercially and open source available. The upscaler that I am going to introduce you is open source #SUPIR and the model is free to use. SUPIR upscaler is many times better than both paid Topaz AI and Magnific AI and you can use this upscaler on your computer for free forever. The difference of SUPIR vs #Topaz and #Magnific is like ages. So in this tutorial you are going to learn everything about how to install, update and use SUPIR upscaler on your personal computer. The video shows Windows but it works perfectly fine on Linux as well.
Scripts Download Link ⤵️
https://www.patreon.com/posts/99176057
Samplers and Text CFG (Text Guidance Scale) Comparison Link ⤵️
https://imgsli.com/MjU2ODQz/2/1
How to install accurate Python, Git and FFmpeg on Windows Tutorial ⤵️
https://youtu.be/-NjNy7afOQ0
Full DreamBooth / Fine-tuning Tutorial ⤵️
https://youtu.be/0t5l6CP9eBg
Scaling Up to Excellence: Practicing Model Scaling for Photo-Realistic Image Restoration In the Wild : https://arxiv.org/abs/2401.13627
Authors introduce SUPIR (Scaling-UP Image Restoration), a groundbreaking image restoration method that harnesses generative prior and the power of model scaling up. Leveraging multi-modal techniques and advanced generative prior, SUPIR marks a significant advance in intelligent and realistic image restoration. As a pivotal catalyst within SUPIR, model scaling dramatically enhances its capabilities and demonstrates new potential for image restoration. Authors collect a dataset comprising 20 million high-resolution, high-quality images for model training, each enriched with descriptive text annotations. SUPIR provides the capability to restore images guided by textual prompts, broadening its application scope and potential
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- 9 replies
posted
an
update
3 months ago
Post
3669
Watch the full tutorial here : https://youtu.be/0t5l6CP9eBg
The tutorial is over 2 hours literally with manually fixed captions and perfect video chapters.
Most Awaited Full Fine Tuning (with DreamBooth effect) Tutorial Generated Images - Full Workflow Shared In The Comments - NO Paywall This Time - Explained OneTrainer - Cumulative Experience of 16 Months Stable Diffusion
In this tutorial, I am going to show you how to install OneTrainer from scratch on your computer and do a Stable Diffusion SDXL (Full Fine-Tuning 10.3 GB VRAM) and SD 1.5 (Full Fine-Tuning 7GB VRAM) based models training on your computer and also do the same training on a very cheap cloud machine from MassedCompute if you don't have such computer.
Tutorial Readme File ⤵️
https://github.com/FurkanGozukara/Stable-Diffusion/blob/main/Tutorials/OneTrainer-Master-SD-1_5-SDXL-Windows-Cloud-Tutorial.md
Register Massed Compute From Below Link (could be necessary to use our Special Coupon for A6000 GPU for 31 cents per hour) ⤵️
https://bit.ly/Furkan-Gözükara
Coupon Code for A6000 GPU is : SECourses
0:00 Introduction to Zero-to-Hero Stable Diffusion (SD) Fine-Tuning with OneTrainer (OT) tutorial
3:54 Intro to instructions GitHub readme
4:32 How to register Massed Compute (MC) and start virtual machine (VM)
5:48 Which template to choose on MC
6:36 How to apply MC coupon
8:41 How to install OT on your computer to train
9:15 How to verify your Python, Git, FFmpeg and Git installation
12:00 How to install ThinLinc and start using your MC VM
12:26 How to setup folder synchronization and file sharing between your computer and MC VM
13:56 End existing session in ThinClient
14:06 How to turn off MC VM
14:24 How to connect and start using VM
14:41 When use end existing session
16:38 How to download very best OT preset training configuration for SD 1.5 & SDXL models
18:00 How to load configuration preset
18:38 Full explanation of OT configuration and best hyper parameters for SDXL
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.
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The tutorial is over 2 hours literally with manually fixed captions and perfect video chapters.
Most Awaited Full Fine Tuning (with DreamBooth effect) Tutorial Generated Images - Full Workflow Shared In The Comments - NO Paywall This Time - Explained OneTrainer - Cumulative Experience of 16 Months Stable Diffusion
In this tutorial, I am going to show you how to install OneTrainer from scratch on your computer and do a Stable Diffusion SDXL (Full Fine-Tuning 10.3 GB VRAM) and SD 1.5 (Full Fine-Tuning 7GB VRAM) based models training on your computer and also do the same training on a very cheap cloud machine from MassedCompute if you don't have such computer.
Tutorial Readme File ⤵️
https://github.com/FurkanGozukara/Stable-Diffusion/blob/main/Tutorials/OneTrainer-Master-SD-1_5-SDXL-Windows-Cloud-Tutorial.md
Register Massed Compute From Below Link (could be necessary to use our Special Coupon for A6000 GPU for 31 cents per hour) ⤵️
https://bit.ly/Furkan-Gözükara
Coupon Code for A6000 GPU is : SECourses
0:00 Introduction to Zero-to-Hero Stable Diffusion (SD) Fine-Tuning with OneTrainer (OT) tutorial
3:54 Intro to instructions GitHub readme
4:32 How to register Massed Compute (MC) and start virtual machine (VM)
5:48 Which template to choose on MC
6:36 How to apply MC coupon
8:41 How to install OT on your computer to train
9:15 How to verify your Python, Git, FFmpeg and Git installation
12:00 How to install ThinLinc and start using your MC VM
12:26 How to setup folder synchronization and file sharing between your computer and MC VM
13:56 End existing session in ThinClient
14:06 How to turn off MC VM
14:24 How to connect and start using VM
14:41 When use end existing session
16:38 How to download very best OT preset training configuration for SD 1.5 & SDXL models
18:00 How to load configuration preset
18:38 Full explanation of OT configuration and best hyper parameters for SDXL
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replied to
their
post
3 months ago
thanks a lot
posted
an
update
3 months ago
Post
1992
Compared Effect Of Image Captioning For SDXL Fine-tuning / DreamBooth Training for a Single Person, 10.3 GB VRAM via OneTrainer
Sadly the post character count is limited so please read full info on Medium here
https://medium.com/@furkangozukara/compared-effect-of-image-captioning-for-sdxl-fine-tuning-dreambooth-training-for-a-single-person-961087e42334
Sadly the post character count is limited so please read full info on Medium here
https://medium.com/@furkangozukara/compared-effect-of-image-captioning-for-sdxl-fine-tuning-dreambooth-training-for-a-single-person-961087e42334
replied to
their
post
3 months ago
I did over 100 trainings empirically to find best hyper parameters. And training U-NET + Text Encoder 1 yields better results that only U-NET @researcher171473
posted
an
update
3 months ago
Post
1886
Now You Can Full Fine Tune / DreamBooth Stable Diffusion XL (SDXL) with only 10.3 GB VRAM via OneTrainer — Both U-NET and Text Encoder 1 is trained — Compared 14 GB config vs slower 10.3 GB Config
Full config and instructions are shared here : https://www.patreon.com/posts/96028218
Used SG161222/RealVisXL_V4.0 as a base model and OneTrainer to train on Windows 10 : https://github.com/Nerogar/OneTrainer
The posted example x/y/z checkpoint comparison images are not cherry picked. So I can get perfect images with multiple tries.
Trained 150 epochs, 15 images and used my ground truth 5200 regularization images : https://www.patreon.com/posts/massive-4k-woman-87700469
In each epoch only 15 of regularization images used to make DreamBooth training affect
As a caption only “ohwx man” is used, for regularization images just “man”
You can download configs and full instructions here : https://www.patreon.com/posts/96028218
Hopefully full public tutorial coming within 2 weeks. I will show all configuration as well
The tutorial will be on our channel : https://www.youtube.com/SECourses
Training speeds are as below thus durations:
RTX 3060 — slow preset : 3.72 second / it thus 15 train images 150 epoch 2 (reg images concept) : 4500 steps = 4500 3.72 / 3600 = 4.6 hours
RTX 3090 TI — slow preset : 1.58 second / it thus : 4500 * 1.58 / 3600 = 2 hours
RTX 3090 TI — fast preset : 1.45 second / it thus : 4500 * 1.45 / 3600 = 1.8 hours
A quick tutorial for how to use concepts in OneTrainer : https://youtu.be/yPOadldf6bI
Full config and instructions are shared here : https://www.patreon.com/posts/96028218
Used SG161222/RealVisXL_V4.0 as a base model and OneTrainer to train on Windows 10 : https://github.com/Nerogar/OneTrainer
The posted example x/y/z checkpoint comparison images are not cherry picked. So I can get perfect images with multiple tries.
Trained 150 epochs, 15 images and used my ground truth 5200 regularization images : https://www.patreon.com/posts/massive-4k-woman-87700469
In each epoch only 15 of regularization images used to make DreamBooth training affect
As a caption only “ohwx man” is used, for regularization images just “man”
You can download configs and full instructions here : https://www.patreon.com/posts/96028218
Hopefully full public tutorial coming within 2 weeks. I will show all configuration as well
The tutorial will be on our channel : https://www.youtube.com/SECourses
Training speeds are as below thus durations:
RTX 3060 — slow preset : 3.72 second / it thus 15 train images 150 epoch 2 (reg images concept) : 4500 steps = 4500 3.72 / 3600 = 4.6 hours
RTX 3090 TI — slow preset : 1.58 second / it thus : 4500 * 1.58 / 3600 = 2 hours
RTX 3090 TI — fast preset : 1.45 second / it thus : 4500 * 1.45 / 3600 = 1.8 hours
A quick tutorial for how to use concepts in OneTrainer : https://youtu.be/yPOadldf6bI
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- 5 replies
replied to
their
post
4 months ago
100% this is next level. thanks for comment @ajibawa-2023
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post
4 months ago
@ameerazam08 100%. I am talking with original developers for CPU Offloading too if they hopefully add.
posted
an
update
4 months ago
Post
I have dedicated several days, working over 12 hours each day, on SUPIR (Scaling-UP Image Restoration), a cutting-edge image enhancement and upscaling model introduced in the paper Scaling Up to Excellence: Practicing Model Scaling for Photo-Realistic Image Restoration In the Wild.
This model is simply mind-blowing. At the bottom of this post, you will see side-by-side comparisons of SUPIR versus the extremely expensive online service, Magnific AI. Magnific is known to be the best among the community. However, SUPIR is by far superior. SUPIR also significantly outperforms Topaz AI upscale. SUPIR manages to remain faithful to the original image almost 100% while adding details and achieving super upscaling with the best realism.
You can read the full blog post here : https://huggingface.co/blog/MonsterMMORPG/supir-sota-image-upscale-better-than-magnific-ai
This model is simply mind-blowing. At the bottom of this post, you will see side-by-side comparisons of SUPIR versus the extremely expensive online service, Magnific AI. Magnific is known to be the best among the community. However, SUPIR is by far superior. SUPIR also significantly outperforms Topaz AI upscale. SUPIR manages to remain faithful to the original image almost 100% while adding details and achieving super upscaling with the best realism.
You can read the full blog post here : https://huggingface.co/blog/MonsterMMORPG/supir-sota-image-upscale-better-than-magnific-ai
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- 4 replies
posted
an
update
4 months ago
Post
Compared Stable Diffusion 3 with Dall-E3 and results are mind blowing.
SD 3 can follow prompts many times better than SD 1.5 or SDXL. It is even better than Dall-E3 in following text / spelling prompts.
The realism of the SD 3 can't be even compared with Dall-E3, since every Dall-E3 output is like a digital render.
Can't wait to get approved of Stability AI early preview program to do more intensive testing.
Some people says be skeptical about cherry picking. I agree but I hope that these Stability AI released images are not that heavy cherry picking.
You can see SD3 vs Dall-E3 comparison here : https://youtu.be/DJxodszsERo
SD 3 can follow prompts many times better than SD 1.5 or SDXL. It is even better than Dall-E3 in following text / spelling prompts.
The realism of the SD 3 can't be even compared with Dall-E3, since every Dall-E3 output is like a digital render.
Can't wait to get approved of Stability AI early preview program to do more intensive testing.
Some people says be skeptical about cherry picking. I agree but I hope that these Stability AI released images are not that heavy cherry picking.
You can see SD3 vs Dall-E3 comparison here : https://youtu.be/DJxodszsERo
posted
an
update
5 months ago
Post
Today my RunPod pod was broken and I didn't notice until I fully did setup it. So I have written the following tutorial for how to deploy a Pod and also verify it is not broken.
You can read on:
Patreon (public) : https://www.patreon.com/posts/how-to-deploy-on-97919576
Medium (public) : https://medium.com/@furkangozukara/how-to-deploy-a-pod-on-runpod-and-verify-it-is-working-20e47031c0b5
CivitAI (public) : https://civitai.com/articles/3994/how-to-deploy-a-pod-on-runpod-and-verify-it-is-working
LinkedIn (public) : https://www.linkedin.com/pulse/how-deploy-pod-runpod-verify-working-furkan-g%2525C3%2525B6z%2525C3%2525BCkara-lgplf%3FtrackingId=EuNOjpKCSQ%252BVfpiQV3D6KQ%253D%253D/?trackingId=EuNOjpKCSQ%2BVfpiQV3D6KQ%3D%3D
Dev . to (public) : https://dev.to/furkangozukara/how-to-deploy-a-pod-on-runpod-and-verify-it-is-working-3pop
You can read on:
Patreon (public) : https://www.patreon.com/posts/how-to-deploy-on-97919576
Medium (public) : https://medium.com/@furkangozukara/how-to-deploy-a-pod-on-runpod-and-verify-it-is-working-20e47031c0b5
CivitAI (public) : https://civitai.com/articles/3994/how-to-deploy-a-pod-on-runpod-and-verify-it-is-working
LinkedIn (public) : https://www.linkedin.com/pulse/how-deploy-pod-runpod-verify-working-furkan-g%2525C3%2525B6z%2525C3%2525BCkara-lgplf%3FtrackingId=EuNOjpKCSQ%252BVfpiQV3D6KQ%253D%253D/?trackingId=EuNOjpKCSQ%2BVfpiQV3D6KQ%3D%3D
Dev . to (public) : https://dev.to/furkangozukara/how-to-deploy-a-pod-on-runpod-and-verify-it-is-working-3pop