Aakash Khadikar's picture
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Aakash Khadikar

Aakashk
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reacted to MonsterMMORPG's post with 🔥 11 months ago
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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