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Updated Stable Diffusion A1111 2023 Installation Tutorial V1.5, V2.1, and Custom Models
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SDXL is out and the only thing you will do differently is put the SDXL Base mode v1.0 and Refiner Model v1.0 into your model's folder the same as you would with any model (i.e. that's where your 1.5 and 2.1 model went) and then generate txt2img using the base model. To use the refiner send your generated image to img2img, choose the refiner model, match the resolution to the txt2img pic, and then set a low denoise (0.1-0.3) and generate.
Here are thew new SDXL models.
This is an updated guide for Installing Stable Diffusion Automatic 1111 (A1111) v1.5, v2.1, and Custom models. Some things have changed recently and installing will slightly easier now we don't have to add yaml config files manually.
Things you will install in order:
Step 1. Install Python 3.10.6 & GIT (do not download updated versions of python)
Step 2. Download A1111 repository & models
Choose pip for package & 11.8 for CUDA
Some useful ARGS
--xformers
--medvram
--no-half
--precision full
==========================
Chapters
00:00 Intro: What has changed & what will be in this video
00:36 PreReqs
00:55 Install Python 3.10.6, GIT, & optional CUDA
02:13 Download Automatic 1111 GitHub Repository to your PC
03:30 Download V1.5, 2.1, & Custom Model & What's EMA vs. Non EMA and Safetensor vs. CKPT
05:40 Bring your Models into Stable diffusion/Models/Stable-Diffusion Folder
09:23 How do you run this thing and generate images?
09:50 Txt2Img Tab the Main tab to create images overview
11:38 Example of Restore Faces + Hires Fix
12:04 CFG Scale
12:28 Seeds
12:49 Img2img
13:05 Denoising
13:43 Inpainting
14:12 What is CLIP?
14:42 Extras Tab (Upscaling and GFPGAN) & Example
Seems like I didn't go over upscaling in the extras tab. It increases the quality and resolution of your base image, just throw it in there and select the number of times you want to increase the resolution. I personally do a latent upscale instead which uses Img2Img w/ denoising under 0.40 and I double the resolution. It will recreate some of the finer details and make the picture look even better.
#Automatic1111 #A1111 #StableDiffusion #StableDiffusiontutorial #stablediffusionaitutorial #aiart #aiartcommunity
Here are thew new SDXL models.
This is an updated guide for Installing Stable Diffusion Automatic 1111 (A1111) v1.5, v2.1, and Custom models. Some things have changed recently and installing will slightly easier now we don't have to add yaml config files manually.
Things you will install in order:
Step 1. Install Python 3.10.6 & GIT (do not download updated versions of python)
Step 2. Download A1111 repository & models
Choose pip for package & 11.8 for CUDA
Some useful ARGS
--xformers
--medvram
--no-half
--precision full
==========================
Chapters
00:00 Intro: What has changed & what will be in this video
00:36 PreReqs
00:55 Install Python 3.10.6, GIT, & optional CUDA
02:13 Download Automatic 1111 GitHub Repository to your PC
03:30 Download V1.5, 2.1, & Custom Model & What's EMA vs. Non EMA and Safetensor vs. CKPT
05:40 Bring your Models into Stable diffusion/Models/Stable-Diffusion Folder
09:23 How do you run this thing and generate images?
09:50 Txt2Img Tab the Main tab to create images overview
11:38 Example of Restore Faces + Hires Fix
12:04 CFG Scale
12:28 Seeds
12:49 Img2img
13:05 Denoising
13:43 Inpainting
14:12 What is CLIP?
14:42 Extras Tab (Upscaling and GFPGAN) & Example
Seems like I didn't go over upscaling in the extras tab. It increases the quality and resolution of your base image, just throw it in there and select the number of times you want to increase the resolution. I personally do a latent upscale instead which uses Img2Img w/ denoising under 0.40 and I double the resolution. It will recreate some of the finer details and make the picture look even better.
#Automatic1111 #A1111 #StableDiffusion #StableDiffusiontutorial #stablediffusionaitutorial #aiart #aiartcommunity
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