stable-diffusion
stable-diffusion
stable-diffusion | stable-diffusion | |
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111 | 382 | |
1,749 | 65,504 | |
- | 1.1% | |
10.0 | 0.0 | |
over 1 year ago | 22 days ago | |
Jupyter Notebook | Jupyter Notebook | |
GNU Affero General Public License v3.0 | GNU General Public License v3.0 or later |
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stable-diffusion
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PSA: You can run your GPU's at 80% power and get the same rendering speeds while saving heat/fan noise/electricity
use or update this one : https://github.com/hlky/stable-diffusion it has all the samplers, and if you want perfect faces, try k_euler_a
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"a software developer after fixing a bug", by DALL-E 2
try this one https://github.com/hlky/stable-diffusion you need at least a 1050 to run it tho
- Which is the best fork out there ?
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At the end of my rope on hlky fork, can anyone recommend any alternative GUI forks I could switch to?
https://github.com/hlky/stable-diffusion/issues/153 With 36 comments and tons of before and after comparisons, which are now deleted
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CUDA memory error with hlky repo, (4GB Nvidia) - any ideas?
I wanted to try hlky version (https://github.com/hlky/stable-diffusion) , due to the WebUI and integration with upscaling models. It should also have the option to be optimized for low VRAM. To avoid getting a green square I have to add the parameters "--precision full --no-half". When I run a prompt, even with the smallest image size, I immediately get a CUDA memory error. Interestingly, without these parameters there isn't any memory error (but, of course, the result is a green square)
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Fallout 5: Toronto (created with AI)
Made using https://github.com/hlky/stable-diffusion
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Just released a Colab notebook that combines Craiyon+Stable Diffusion
Any chance to get this integrated into something like hlky's web ui?
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AI Tekst til bilde: Elg og stavkirke med nordlys over Norsk flagg i bakgrunnen [OC] Mer detaljer i posten
Linux Guide her. Jeg har også Linux, men jeg valgte å sette det opp på Windows boksen min fordi driverne til Nvidia kortet på Linux ikke er helt sammarbeidsvillig når det kommer til å justere viftene etter sensorene i kortet (så jeg må sette det manuelt).
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Using GFPGAN for only the eyes?
I'm seeing GFPGAN essentially remove all texture from faces, and I only want to use it on the eyes. Any thoughts on how to do this? I am using hlky/stable-diffusion now but I have no issues running a different repo/fork if needed and using command line.
- What's the best install of Stable Diffusion right now?
stable-diffusion
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Go is bigger than crab!
Which is a 1-click install of Stable Diffusion with an alternative web interface. You can choose a different approach but this one is pretty simple and I am new to this stuff.
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Why & How to check Invisible Watermark
an invisible watermarking of the outputs, to help viewers identify the images as machine-generated.
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How to create an Image generating AI?
It sounds like you just want to set up Stable Diffusion to run locally. I don't think your computer's specs will be able to do it. You need a graphics card with a decent amount of VRAM. Stable diffusion is in Python as is almost every AI open source project I've seen. If you can get your hands on a system with an Nvidia RTX card with as much VRAM as possible, you're in business. I have an RTX 3060 with 12 gigs of VRAM and I can run stable diffusion and a whole variety of open source LLMs as well as other projects like face swap, Roop, tortoise TTS, sadtalker, etc...
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Two video cards...one dedicated to Stable Diffusion...the other for everything else on my PC?
Use specific GPU on multi GPU systems · Issue #87 · CompVis/stable-diffusion · GitHub
- Automatic1111 - Multiple GPUs
- Ist Google inzwischen einfach unbrauchbar?
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Why are people so against compensation for artists?
I dealt with this in one of my posts. At least SD 1.1 till 1.5 are all trained on a batch size of 2048. The version pretty much everyone uses (1.5) is first pretrained at a resolution of 256x256 for 237K steps on laion2B-en, at the end of those training steps it will have seen roughly 500M images in laion2B-en. After that it is pre-trained for 194K steps on laion-high-resolution at a resolution of 512x512, which is a subset of 170M images from laion5B. Finally it is trained for 1.110K steps on LAION aesthetic v2 5+. This is easily verified by taking a glance at the model card of SD 1.5. Though that one doesn't specify for part of the training exactly which aesthetic set was used for part of the training, for that you have to look at the CompVis github repo. Thus at the end of it all both the most recent images and the majority of images will have come from LAION aesthetic v2 5+ (seeing every image approx 4 times). Realistically a lot of the weights obtained from pretraining on 2B will have been lost, and only provided a good starting point for the weights.
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Is SDXL really open-source?
stable diffusion · CompVis/stable-diffusion@2ff270f · GitHub
- I want to ask the AI to draw me as a Pokemon anime character then draw six of Pokemon of my choice next to me. What are my best free, 15$ or under and 30$ or under choices?
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how can i create my own ai image model
Here for example --> https://github.com/CompVis/stable-diffusion
What are some alternatives?
diffusers-uncensored - Uncensored fork of diffusers
GFPGAN - GFPGAN aims at developing Practical Algorithms for Real-world Face Restoration.
stable-diffusion-krita-plugin
Real-ESRGAN - Real-ESRGAN aims at developing Practical Algorithms for General Image/Video Restoration.
instant-ngp - Instant neural graphics primitives: lightning fast NeRF and more
stable-diffusion - Optimized Stable Diffusion modified to run on lower GPU VRAM
diffusers - 🤗 Diffusers: State-of-the-art diffusion models for image and audio generation in PyTorch and FLAX.
stable_diffusion.openvino
VQGAN-CLIP - Just playing with getting VQGAN+CLIP running locally, rather than having to use colab.
stable-diffusion-webui - Stable Diffusion web UI [Moved to: https://github.com/sd-webui/stable-diffusion-webui]
onnx - Open standard for machine learning interoperability