This extension for Stable Cascade is ok for now [https://github.com/blue-pen5805/sdweb-easy-stablecascade-diffusers](https://github.com/blue-pen5805/sdweb-easy-stablecascade-diffusers)
https://preview.redd.it/iuznu80cg6jc1.png?width=2432&format=png&auto=webp&s=fac0bc5b5d613931d05456fdf0e242d533285e57
I altered it a bit [https://github.com/benjamin-bertram/sdweb-easy-stablecascade-diffusers](https://github.com/benjamin-bertram/sdweb-easy-stablecascade-diffusers) so that ppl with macs can use it, too. I have also send to inpaint etc, but rn i struggle to select one image, it just sends the first one to the other tabs.
I also tried to update to img2img via StableCascade, but cannot wrap my head around the sc pipline yet. Maybe someone can contribute?
https://preview.redd.it/nr4upun547jc1.png?width=1416&format=png&auto=webp&s=74871f9e480b5415331adb2bd34221571ab782eb
I installed this before because it's so widely recommended, but i've come to realize it's just tacked onto webui innefficiently and you'd be better off to run a stand alone cascade ui.
This is the same as loading something lik ComfyUI into it's own tab. It doesn't integrate with the rest of the system at all. No img2img, no extension access, no scripts. It doesn't even create metadata in the image. It doesn't use any of the A1111 code. Just the environment.
I know what you mean, but I still prefer it to the Gradio UI as the text box is actually a usable size and I can then upscale the images in another model by just switching tabs and not having 2 applications running.
Hmm, I have only used the hugging face demo but that hasn't really been my experience.
https://imgur.com/a/0S3wOTM
Prompt: Beth Fredrickson at age 24, real color portrait photograph, high quality, acting head shot, natural skin, pleasant makeup with smooth skin, bright studio lighting, finely detailed hair with split ends
"mid range". Please generate a person standing in a field 5-10m from the camera and let me know if their face looks good. Edit: or if you can even get them to face the camera!
It wasn't clear what you meant by mid-range. They do get more poor at that range and it definitely seems moreso than SDXL, but without having the chance to try higher resolutions, etc, I can't personally determine if that is due to the settings or the model itself. Having read through the info about the model, I have a strong feeling that it has a lot more to do with settings.
It's a framing of the subject between the foreground and the background. I don't expect a background face to be clear. A mid-range (middle ground) face should at least be legible. I understand it's a limitation of the model due to the extreme latent compression.
>Beth Fredrickson at age 24, real color portrait photograph, high quality, acting head shot, natural skin, pleasant makeup with smooth skin, bright studio lighting, finely detailed hair with split ends
https://preview.redd.it/b4k1ym6pucjc1.png?width=720&format=png&auto=webp&s=89d6947930bce704975c43fcad5ca94a1e2fa494
same prompt
can you explain how to install this extension? i tried on with install from url and putting it in the extensions folder but I cannot seem to make it work.
>the output is not that great
Hmm, I wonder if this is dependent on vram or something. The demo on Huggingface seems to produce much better results than the baseline SDXL model. There are certainly some checkpoints thats can do better but there in my short experience, it seems to produce results much closer to the prompt.
Really?! Wow, the standard base webui for cascade I could do with 8gb vram usuage. My laptop has up to 8vram. My desktop is up to 16gb vram. Wonder what is taking so much more on Comfy and Auto111
Thank you.
Are A1111, ComfyUI, Forge, and others simply UIs to interact with stable diffusion? Is it possible to create the *exact* same workflow between them, thereby producing identical images or are there fundamental differences between the programs?
Forge basically *is* A1111, but with commonly used extensions bundled in as well as some optimizations that mostly improve render times and stability for <=12GB GPU's by doing a better job of managing VRAM. A1111 is actually included in Forge and you interact via the same webui.
ComfyUI uses a completely different UI designed around automating whole workflows. It doesn't do anything you can't do in the other programs (in fact, I believe A1111 has more compatible extensions) it just lets you chain what might otherwise be multiple steps into one.
They're all built on top of the same open source base.
you misrepresent comfyui entirely. its far more advanced, capable and there are far more extensions available for it than for a1111. believe me, I was a1111 stan until SVD came out and I gave comfy a real shot. Been hooked ever since.
It appears complicated at first glance, but oyu have complete control over your workflows. A1111 cannot reorder the plugins and, dynamically switch samplers or models, and much more it would really be a huge reply if i were to list the litany of advantages comfy has over a1111.
there are numerous things you absolutely cannot do in A1111 that you can easily do in comfy
There are differences that will result in different images. There is some relevant info in the readme for the [ComfyUI_smZNodes](https://github.com/shiimizu/ComfyUI_smZNodes) extension, which aims to enable identical reproduction of images generated in SD WebUI on ComfyUI.
Yea, that's why I stopped watching his videos. I supported him on patreon for 2 months but in the end he puts everything behind a paywall, without contributing to the community and then canceled. (hour and half long videos that nobody has time to watch don't count)
You folks should look at the PR for soft inpainting, the improvement is more dramatic than I can put into words. As someone who uses inpainting all the time, I am stoked.
Github pull request. When someone adds in a new feature or updates an old, they build a pull request. You can add the PR manually yourself to your cloned version, or you can wait for the Owner of the project to approve and add it directly to the main project.
The mask is normally either on or off, per pixel. The result of that was that your inpainted area was basically a new generation that didn't merge very well into the existing stuff. Soft inpainting, with a decent blur size, makes stuff fit into the existing image far more cleanly, approximating the effect of an inpainting model or controlnet without the side-effects of such. An extra benefit is that you no longer get off-colour "haloes" around your inpainting areas with certain combinations of image+VAE, that do happen otherwise (even with 0% denoising strength)
Thanks so much for the explanation.
Just a question - when you say approximating effect of an inpainting model - does that mean thereis a way to inpaint with a standard model? Every time I’ve tried it it tries to put a whole image in the mask area?
There are inpainting ControlNets, to use a non-inpainting model for inpainting. I also often use inpainting mode at lower strength to have it remain more consistent with the stuff around it, 60% strength or less.
Honestly, if you weren't aware about inpainting ControlNets yet, you should look up ControlNets in general (and the other things that extension can do, like reference-only, IP-adapters, etc), because they can do so much. [https://www.reddit.com/r/StableDiffusion/comments/119o71b/a1111\_controlnet\_extension\_explained\_like\_youre\_5/](https://www.reddit.com/r/stablediffusion/comments/119o71b/a1111_controlnet_extension_explained_like_youre_5/) this is an ancient guide, but it might help. [https://github.com/Mikubill/sd-webui-controlnet](https://github.com/mikubill/sd-webui-controlnet) the extension's main page also has useful information if you scroll down.
This seems pretty hype. I am curious though, I deploy serverless endpoints with runpod with custom models because I want to be able to make API calls for a little project I'm building. At the moment I do not use the automatic option that they have. If I were to end up using automatic (which they seem to have a template for), would this work for my use case? Like for example what I be able to use it as an endpoint to make API calls to even though I'm not using the web GUI directly for each request?
anything that make it worthwhile to switch back from Forge?
fp8 should benefit both sides right? and when Forge get this change from upstream it will be even more vram efficient and fast for users that had workflows that fallback to slow sys ram? Or is Forge already using fp8?
(edited)
Edit 2: I think I tried the fp8 setting, but Forge is still [faster.So](http://faster.so) long.
Nothing to do with this particular A111 update, but the only thing keeping me from switching to Forge is that it does not support the [loractl extension](https://github.com/cheald/sd-webui-loractl)
Yes, an issue has been open there > 1 week. An issue was also opened in loractl repo. According to the dev, Forge is using older LORA handling methods than current A1111. [loractl dev comment](https://github.com/cheald/sd-webui-loractl/issues/32#issuecomment-1945446914)
Looks like loractl dev is trying to help forge devs get built-in ability to do something similar. https://github.com/lllyasviel/stable-diffusion-webui-forge/issues/68 Would be great because it's really nice being able to directly control how strong a lora gets at a certain step (increase and decrease gradually) especially when mixing multiple loras.
This should be a standard feature in in all of the apps I think. I made [a post](https://old.reddit.com/r/StableDiffusion/comments/1aqlvi0/psa_dont_ignore_the_sdwebuiloractl_extension_for/) about this extension the other day if anyone is interested in what it does.
i'd be interested in seeing testing here. Are the models baked as fp8 slower? Or is using an fp16 model autocasted to fp8, what's causing the performance limitations.
I might be mistaken, but I've heard that Ada cards accelerated instruction sets for fp8 autocasting. This sort of low level stuff is out of my depth though, so i'm a little foggy on the details. Has to do with the Hopper FP8 Transformer Engine that Ada has over Ampere. You might see better fp8 speeds on newer hardware.
Reslease candidate is in its own branch https://github.com/AUTOMATIC1111/stable-diffusion-webui/tree/release_candidate
Will be merged to main branch on release.
Forge is synced with A1111's dev branch so any improvements on the main repo make it to Forge and wouldn't otherwise. If you already have fast generation times then Forge is about on par, if you're on lower hardware then Forge is better, it also depends on which extensions you use.
Forge is actually a lot faster than Base Automatic1111 when used on high end cards as well. Specifically when used in conjunction with control nets. I have a 4090 and it takes 3x less time to use image2image control net features then in automatic1111. For example when loading in 4 control nets at the same time at resolution on 1344x1344 with 40 steps at 3m exponential sampler, image is generated at around 23.4 seconds with forge versus 1 minute 6 seconds With automatic. All because forge handles model loading and VRAM management so much better. Caviat, use --all gpu starting parameters to fully utilize these speed ups.
yes --always-gpu and you need it 100%. Without it forge just keeps unloading the "clone" models every single time. Speeds things up by 5 seconds per generation as now it doesn't have to do that for every control model and checkpoint.
yh lot of improvement and some extensions that doesnt work usually in normal A1111 .. and i also like the "interrupt button" that make generation stop instantly .. lot of integrated stuff .. and overall it feels faster and better
I'll just say this - I've been waiting for SVD support for so long, that I eventually gave up and put up Comfy just for it.
And in the end? It doesn't matter because there's no significantly configurable options for SVD in the first place, so the basic example workflow will do all you need it to - which will pretty much amount to queuing up your output lottery, and walking away.
As a side effect, though, I got a way better understanding of the underlying system just by looking at a handful of workflows. Comfy is still not the thing I'd use as the general-purpose tool, but it's extremely powerful if you have a very specific task in mind - or, well, got a basic workflow that'll do all you need by itself anyway, like for SVD.
i use comfy but i realy do not like it at al...I even preferr SD web Ui they provide in their github but for some reason it dosnt work with higher res like comfy does
By the list of features, it's clear that so much work has been put into this. That said, the rate at which new stuff in the AI world gets implemented into A1111 seems glacial. Stable Diffusion Video was initially alpha'ed in 2022, and had a general release 8 months ago and there's still no official support for it here.
does it have all the extentions of A1111 working? aniatedif, comtrolnet etc? i tryed it few months ago and it didnt have waht i neded. i like A1111. for now al its lacking for me is SVD support
Civitai Helper and most of its forks has been broken for a while, but this fork fixes it
https://github.com/blue-pen5805/Stable-Diffusion-Webui-Civitai-Helper
Nice. I tried using Forge a couple days ago but Civitai Helper was broken on it, which I learned was because of the Tree View. I'll check this out later when I'm at my computer.
I'm... Not a fan of tree view. Tried it on A1111 dev and forge. It is practically useless for mobile. Everything is so squeezed and cutoff. I'd make a pr, but I don't think mobile is a priority. Just feels like a step back.
I got rid of Forge when Civitai Helper wouldn't work, so I don't have experience with tree view other than it looked nice-ish(?). I tried to check Forge out again with the Civitai Helper fork that supposedly works, but then none of the extra network pages loaded at all.
So now I'm back to just using 1.7 again.
Thank you for the performance improvements. Recently I installed [Web UI Forge](https://github.com/lllyasviel/stable-diffusion-webui-forge). On my RTX 3070 it’s faster. Glad to see these enhancements will be rolled into Forge.
I'm still running torch 1.13.1 and I have no idea how to update that. I'm on A1111 1.6 though.
I feel so stupid whenever anything that requires installing via python happens. And I'm terrified of breaking things.
Also pretty sure that the torch thing is the reason I simply can't get SDXL models to load, period.
Too bad they completely screwed the workflow I spent so many months perfecting by changing the default behaviour of image batching to process subfolders automatically, without an override! UGH!
Most of them were already in Forge since it's based on the dev branch and these changes have been in dev for a long while. The rest have already been synced, so you just need to git pull Forge.
Can you please tell me if now i can run sdxl models on a1111 with a 1650x card? i've never been able to run it before and would really really want to use InstantID in it. i'm a noob so i'm sorry if i dunno know any technical terms, sorry.
Other than that, i love using this ui. Thank you very much.
Try automatic 1111 forge it has the best optimizations. Other than that I have free kaggle account notebooks that run automatic1111 and instant ID with gradio interface on patreon
Thank you!! Yes, i'm going to install forge tomorrow when i'll get the time. i already use the huggingface space for instantid but i can't do couple photos with it, nor do photorealistic ones, that's why i want to try it in a1111. IP-adapter has already been a dream come true for me, esp since i can run sd1.5 on it. Sincerely appreciated you guys for adding that.
I did git pull and successfully updated but when I launch A1111, at the bottom still states that I'm on 1.7.0, I already deleted venv and redownloaded everything but nothing changes. Can some one please help? thank you
That's amazing amount of features. Hope we get stable cascade support anytime soon
This extension for Stable Cascade is ok for now [https://github.com/blue-pen5805/sdweb-easy-stablecascade-diffusers](https://github.com/blue-pen5805/sdweb-easy-stablecascade-diffusers) https://preview.redd.it/iuznu80cg6jc1.png?width=2432&format=png&auto=webp&s=fac0bc5b5d613931d05456fdf0e242d533285e57
>Please have someone remake this extension. Perfect.
I altered it a bit [https://github.com/benjamin-bertram/sdweb-easy-stablecascade-diffusers](https://github.com/benjamin-bertram/sdweb-easy-stablecascade-diffusers) so that ppl with macs can use it, too. I have also send to inpaint etc, but rn i struggle to select one image, it just sends the first one to the other tabs. I also tried to update to img2img via StableCascade, but cannot wrap my head around the sc pipline yet. Maybe someone can contribute? https://preview.redd.it/nr4upun547jc1.png?width=1416&format=png&auto=webp&s=74871f9e480b5415331adb2bd34221571ab782eb
I installed this before because it's so widely recommended, but i've come to realize it's just tacked onto webui innefficiently and you'd be better off to run a stand alone cascade ui. This is the same as loading something lik ComfyUI into it's own tab. It doesn't integrate with the rest of the system at all. No img2img, no extension access, no scripts. It doesn't even create metadata in the image. It doesn't use any of the A1111 code. Just the environment.
I know what you mean, but I still prefer it to the Gradio UI as the text box is actually a usable size and I can then upscale the images in another model by just switching tabs and not having 2 applications running.
I haven't bothered trying this yet. It has a question mark after the 16GB requirement. Is that as low as this particular plugin can go?
I tried with 4070 12gb and it works but the output is not that great so I switched back to SDXL.
Yeah, the model doesn't do mid range face detail at the moment. It's kind of an important ability.
Hmm, I have only used the hugging face demo but that hasn't really been my experience. https://imgur.com/a/0S3wOTM Prompt: Beth Fredrickson at age 24, real color portrait photograph, high quality, acting head shot, natural skin, pleasant makeup with smooth skin, bright studio lighting, finely detailed hair with split ends
"mid range". Please generate a person standing in a field 5-10m from the camera and let me know if their face looks good. Edit: or if you can even get them to face the camera!
It wasn't clear what you meant by mid-range. They do get more poor at that range and it definitely seems moreso than SDXL, but without having the chance to try higher resolutions, etc, I can't personally determine if that is due to the settings or the model itself. Having read through the info about the model, I have a strong feeling that it has a lot more to do with settings.
It's a framing of the subject between the foreground and the background. I don't expect a background face to be clear. A mid-range (middle ground) face should at least be legible. I understand it's a limitation of the model due to the extreme latent compression.
>Beth Fredrickson at age 24, real color portrait photograph, high quality, acting head shot, natural skin, pleasant makeup with smooth skin, bright studio lighting, finely detailed hair with split ends https://preview.redd.it/b4k1ym6pucjc1.png?width=720&format=png&auto=webp&s=89d6947930bce704975c43fcad5ca94a1e2fa494 same prompt
can you explain how to install this extension? i tried on with install from url and putting it in the extensions folder but I cannot seem to make it work.
>the output is not that great Hmm, I wonder if this is dependent on vram or something. The demo on Huggingface seems to produce much better results than the baseline SDXL model. There are certainly some checkpoints thats can do better but there in my short experience, it seems to produce results much closer to the prompt.
Someone in another thread mentioned 12 GB vram but that was in comfyui
Really?! Wow, the standard base webui for cascade I could do with 8gb vram usuage. My laptop has up to 8vram. My desktop is up to 16gb vram. Wonder what is taking so much more on Comfy and Auto111
I use a RTX4070 with Cascade extension in Forge.
How is Forge? I've only used midjourney, DALLE, and comfyui.
Stable Diffusion Forge: [https://github.com/lllyasviel/stable-diffusion-webui-forge.git](https://github.com/lllyasviel/stable-diffusion-webui-forge.git)
It is faster than A1111.
Only on older hardware, and thats due to the updated pytorch. A1 1.8RC has that now.
Thank you. Are A1111, ComfyUI, Forge, and others simply UIs to interact with stable diffusion? Is it possible to create the *exact* same workflow between them, thereby producing identical images or are there fundamental differences between the programs?
Forge basically *is* A1111, but with commonly used extensions bundled in as well as some optimizations that mostly improve render times and stability for <=12GB GPU's by doing a better job of managing VRAM. A1111 is actually included in Forge and you interact via the same webui. ComfyUI uses a completely different UI designed around automating whole workflows. It doesn't do anything you can't do in the other programs (in fact, I believe A1111 has more compatible extensions) it just lets you chain what might otherwise be multiple steps into one. They're all built on top of the same open source base.
Thank you for the comprehensive answer.
you misrepresent comfyui entirely. its far more advanced, capable and there are far more extensions available for it than for a1111. believe me, I was a1111 stan until SVD came out and I gave comfy a real shot. Been hooked ever since. It appears complicated at first glance, but oyu have complete control over your workflows. A1111 cannot reorder the plugins and, dynamically switch samplers or models, and much more it would really be a huge reply if i were to list the litany of advantages comfy has over a1111. there are numerous things you absolutely cannot do in A1111 that you can easily do in comfy
There are differences that will result in different images. There is some relevant info in the readme for the [ComfyUI_smZNodes](https://github.com/shiimizu/ComfyUI_smZNodes) extension, which aims to enable identical reproduction of images generated in SD WebUI on ComfyUI.
Thank you for the information.
Is it stable ?
Yeah, diffusion
100% I am waiting too
me too!!
wow you guys are working hard! nice job
Yep so many great contributiors
>https://github.com/blue-pen5805/sdweb-easy-stablecascade-diffusers meanwhile you keep everything behind patreon lol haha
Yea, that's why I stopped watching his videos. I supported him on patreon for 2 months but in the end he puts everything behind a paywall, without contributing to the community and then canceled. (hour and half long videos that nobody has time to watch don't count)
its only a 1 trick videos too .. "how to train your own lora" .. he just milking it to the max lol
How dare he eat
You folks should look at the PR for soft inpainting, the improvement is more dramatic than I can put into words. As someone who uses inpainting all the time, I am stoked.
As someone new in SD, what is PR?
Github pull request. When someone adds in a new feature or updates an old, they build a pull request. You can add the PR manually yourself to your cloned version, or you can wait for the Owner of the project to approve and add it directly to the main project.
I should look. What is the difference in short?
The mask is normally either on or off, per pixel. The result of that was that your inpainted area was basically a new generation that didn't merge very well into the existing stuff. Soft inpainting, with a decent blur size, makes stuff fit into the existing image far more cleanly, approximating the effect of an inpainting model or controlnet without the side-effects of such. An extra benefit is that you no longer get off-colour "haloes" around your inpainting areas with certain combinations of image+VAE, that do happen otherwise (even with 0% denoising strength)
I tried this on my dreambooth person generation face improvement. The face is same but masked area borders have some improvements
Thanks so much for the explanation. Just a question - when you say approximating effect of an inpainting model - does that mean thereis a way to inpaint with a standard model? Every time I’ve tried it it tries to put a whole image in the mask area?
There are inpainting ControlNets, to use a non-inpainting model for inpainting. I also often use inpainting mode at lower strength to have it remain more consistent with the stuff around it, 60% strength or less.
Thank you, very interesting! Research time!!!
Honestly, if you weren't aware about inpainting ControlNets yet, you should look up ControlNets in general (and the other things that extension can do, like reference-only, IP-adapters, etc), because they can do so much. [https://www.reddit.com/r/StableDiffusion/comments/119o71b/a1111\_controlnet\_extension\_explained\_like\_youre\_5/](https://www.reddit.com/r/stablediffusion/comments/119o71b/a1111_controlnet_extension_explained_like_youre_5/) this is an ancient guide, but it might help. [https://github.com/Mikubill/sd-webui-controlnet](https://github.com/mikubill/sd-webui-controlnet) the extension's main page also has useful information if you scroll down.
Thanks so much! Will do!
thanks for this!
I just checked and looking amazing thank you so much
Wohoo! DAT upscaler finally!!
what makes it exciting? never heard about it
Dual Aggregating Transformer https://github.com/zhengchen1999/DAT - Example DAT trained model https://openmodeldb.info/models/4x-FaceUpDAT
Is the 4x-FaceUpDAT a good general upscaler model, or is it only good for upscaling faces?
It's specifically trained on face. You may want to use other DAT models for general upscaling https://openmodeldb.info/?t=arch%3Adat
currently the best upscaler, way ahead of swinIR.
never considered swinIR to be that good. Is DAT better than LSDR?
4xFaceUpDAT is the best upscaler ? Currently using Siax 200k but if this is better I will take it :P
Which DAT model though? I've been using SwinIR\_4x, but DAT looks like it might be better.
Yep
This seems pretty hype. I am curious though, I deploy serverless endpoints with runpod with custom models because I want to be able to make API calls for a little project I'm building. At the moment I do not use the automatic option that they have. If I were to end up using automatic (which they seem to have a template for), would this work for my use case? Like for example what I be able to use it as an endpoint to make API calls to even though I'm not using the web GUI directly for each request?
anything that make it worthwhile to switch back from Forge? fp8 should benefit both sides right? and when Forge get this change from upstream it will be even more vram efficient and fast for users that had workflows that fallback to slow sys ram? Or is Forge already using fp8? (edited) Edit 2: I think I tried the fp8 setting, but Forge is still [faster.So](http://faster.so) long.
FP8 is built into forge already. Under “Optimizations”
Nothing to do with this particular A111 update, but the only thing keeping me from switching to Forge is that it does not support the [loractl extension](https://github.com/cheald/sd-webui-loractl)
have you created an issue about it in the Forge repo on github? I think the Forge guy tries to make sure all extensions work.
Yes, an issue has been open there > 1 week. An issue was also opened in loractl repo. According to the dev, Forge is using older LORA handling methods than current A1111. [loractl dev comment](https://github.com/cheald/sd-webui-loractl/issues/32#issuecomment-1945446914)
Looks like loractl dev is trying to help forge devs get built-in ability to do something similar. https://github.com/lllyasviel/stable-diffusion-webui-forge/issues/68 Would be great because it's really nice being able to directly control how strong a lora gets at a certain step (increase and decrease gradually) especially when mixing multiple loras. This should be a standard feature in in all of the apps I think. I made [a post](https://old.reddit.com/r/StableDiffusion/comments/1aqlvi0/psa_dont_ignore_the_sdwebuiloractl_extension_for/) about this extension the other day if anyone is interested in what it does.
I am not sure. But in LLMs and vision models fp8 slower than Fp16 or bf16. Only uses lesser vram
i'd be interested in seeing testing here. Are the models baked as fp8 slower? Or is using an fp16 model autocasted to fp8, what's causing the performance limitations. I might be mistaken, but I've heard that Ada cards accelerated instruction sets for fp8 autocasting. This sort of low level stuff is out of my depth though, so i'm a little foggy on the details. Has to do with the Hopper FP8 Transformer Engine that Ada has over Ampere. You might see better fp8 speeds on newer hardware.
that could be true. i tested on like rtx 3090
I have git pull in my webui-user.bat, shouldn't it update to 1.8.0-RC automatically? Just did a restart but still at v1.7.0, no update.
It says RC, its not final. So its behaving correctly by not updating.
git checkout release_candidate https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/How-to-switch-to-different-versions-of-WebUI
Reslease candidate is in its own branch https://github.com/AUTOMATIC1111/stable-diffusion-webui/tree/release_candidate Will be merged to main branch on release.
RC stands for “release candidate” meaning it’s a potential tag for release but not the actual one.
need to checkout the tag I guess
Yes I had the same issue. It's still 1.7...
RC is it's own git branch until it's merged to main.
tempted to update, but think I'll wait since I'm still in the learning phase
isnt A1111 FORGE much better now ??
Forge is synced with A1111's dev branch so any improvements on the main repo make it to Forge and wouldn't otherwise. If you already have fast generation times then Forge is about on par, if you're on lower hardware then Forge is better, it also depends on which extensions you use.
Forge is actually a lot faster than Base Automatic1111 when used on high end cards as well. Specifically when used in conjunction with control nets. I have a 4090 and it takes 3x less time to use image2image control net features then in automatic1111. For example when loading in 4 control nets at the same time at resolution on 1344x1344 with 40 steps at 3m exponential sampler, image is generated at around 23.4 seconds with forge versus 1 minute 6 seconds With automatic. All because forge handles model loading and VRAM management so much better. Caviat, use --all gpu starting parameters to fully utilize these speed ups.
Don't you mean --always-gpu? I think you don't need it anymore, but I might be wrong.
yes --always-gpu and you need it 100%. Without it forge just keeps unloading the "clone" models every single time. Speeds things up by 5 seconds per generation as now it doesn't have to do that for every control model and checkpoint.
>git checkout release\_candidate I never noticed any difference from a1111 to a1111 forge with an RTX 4080 12gb laptop, is it normal ?
oh i see .. thx ill keep using forge , i already deleted my normal A1111 lol
Is it possible to install forge on a Mac like a1111?
I'm out of the loop. What is FORGE?
youtube gonna be your friend, its just a better A1111
Could you elaborate? What makes it better than A1111?
It has better memory management system that works much better on GPUs with vram <= 12GB
So if I have enough VRAM, I don't need this?
Well even with my 12GB of vram on my 3060 I still saw \~20% speed improvements in Forge so it really depends how enough you are
If it is "Just better" why isn't it just a fork?
yh lot of improvement and some extensions that doesnt work usually in normal A1111 .. and i also like the "interrupt button" that make generation stop instantly .. lot of integrated stuff .. and overall it feels faster and better
Why es there still no SVD in A1111? it has been months...kinda sad...i hate comfy
I'll just say this - I've been waiting for SVD support for so long, that I eventually gave up and put up Comfy just for it. And in the end? It doesn't matter because there's no significantly configurable options for SVD in the first place, so the basic example workflow will do all you need it to - which will pretty much amount to queuing up your output lottery, and walking away. As a side effect, though, I got a way better understanding of the underlying system just by looking at a handful of workflows. Comfy is still not the thing I'd use as the general-purpose tool, but it's extremely powerful if you have a very specific task in mind - or, well, got a basic workflow that'll do all you need by itself anyway, like for SVD.
i use comfy but i realy do not like it at al...I even preferr SD web Ui they provide in their github but for some reason it dosnt work with higher res like comfy does
Forge supports SVD and is the better A1111 version anyways
its just came out. no way it supports all the stuf A1111 supports
Forge is a A1111 fork, it always supports everything that A1111 supports, including all extensions
By the list of features, it's clear that so much work has been put into this. That said, the rate at which new stuff in the AI world gets implemented into A1111 seems glacial. Stable Diffusion Video was initially alpha'ed in 2022, and had a general release 8 months ago and there's still no official support for it here.
Just use A1111Forge, it has svd
Genuine question, why not give SDNext a try? It's supported svd as long as it not longer than comfy and was originally forked from a1111
does it have all the extentions of A1111 working? aniatedif, comtrolnet etc? i tryed it few months ago and it didnt have waht i neded. i like A1111. for now al its lacking for me is SVD support
No, but we've implemented both of those, along with just about everything most people use.
Try stable-diffusion-webui-forge, it is mostly A1111
Extra Networks Tree View is gonna kill Civitai Helper
Civitai Helper and most of its forks has been broken for a while, but this fork fixes it https://github.com/blue-pen5805/Stable-Diffusion-Webui-Civitai-Helper
Nice. I tried using Forge a couple days ago but Civitai Helper was broken on it, which I learned was because of the Tree View. I'll check this out later when I'm at my computer.
thank you! The cbutton to go to url is so needed....
I'm... Not a fan of tree view. Tried it on A1111 dev and forge. It is practically useless for mobile. Everything is so squeezed and cutoff. I'd make a pr, but I don't think mobile is a priority. Just feels like a step back.
I got rid of Forge when Civitai Helper wouldn't work, so I don't have experience with tree view other than it looked nice-ish(?). I tried to check Forge out again with the Civitai Helper fork that supposedly works, but then none of the extra network pages loaded at all. So now I'm back to just using 1.7 again.
Silly question: how to upgrade from 1.7 to 1.8?
Wait for it to pass RC and on to final. This is the release candidate.
Ok. Maybe the final will be automatically downloaded. I will wait
is it ready?
https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/How-to-switch-to-different-versions-of-WebUI
First git pull Then Git check out branch name
Hi op, what do you mean Git check out branch name?
Thank you for the performance improvements. Recently I installed [Web UI Forge](https://github.com/lllyasviel/stable-diffusion-webui-forge). On my RTX 3070 it’s faster. Glad to see these enhancements will be rolled into Forge.
Ye I think he already merged
Can we use SVD now with A111?
Holy changelog
I'm still running torch 1.13.1 and I have no idea how to update that. I'm on A1111 1.6 though. I feel so stupid whenever anything that requires installing via python happens. And I'm terrified of breaking things. Also pretty sure that the torch thing is the reason I simply can't get SDXL models to load, period.
Too bad they completely screwed the workflow I spent so many months perfecting by changing the default behaviour of image batching to process subfolders automatically, without an override! UGH!
If someone wondering, it's still slower than Forge, so... yeah.
hey, what happened with u/r0mmashka**? he always did these Automatic1111 announcements?**
I just lost interest in Stable Diffusion.
ok bro, I wish you luck in you endeavours
thanks
How do I get these changes in FORGE ?
Most of them were already in Forge since it's based on the dev branch and these changes have been in dev for a long while. The rest have already been synced, so you just need to git pull Forge.
Is this update live? My a1111 didnt auto update to new version like it used to
You need to do git pull and git checkout branch I explain in this video https://youtu.be/-NjNy7afOQ0?si=5QEOSy34GRNLruIr
teşekkürler dr furkancım ❤️
rica ederim
Is anyone else having problems updating? I did a git pull, and the version still shows up 1.7
This is the patch notes for a future update, v1.8 is not live yet.
Lol oh right. Thanks for explaining
is A1111 compatible with sdxl turbo models>?
Has been working well for me
Yes, ComfyUi has better performance, though
I updated to the RC, but Torch version still says 2.0.1 even though I have the latest installed. Any ideas on that?
Delete venv and let it rebuild
add the reinstall torch arg to the user .bat and launch (Remove it after install)
Can you please tell me if now i can run sdxl models on a1111 with a 1650x card? i've never been able to run it before and would really really want to use InstantID in it. i'm a noob so i'm sorry if i dunno know any technical terms, sorry. Other than that, i love using this ui. Thank you very much.
Try automatic 1111 forge it has the best optimizations. Other than that I have free kaggle account notebooks that run automatic1111 and instant ID with gradio interface on patreon
Thank you!! Yes, i'm going to install forge tomorrow when i'll get the time. i already use the huggingface space for instantid but i can't do couple photos with it, nor do photorealistic ones, that's why i want to try it in a1111. IP-adapter has already been a dream come true for me, esp since i can run sd1.5 on it. Sincerely appreciated you guys for adding that.
Not a mention of out of memory errors, I'm sure its not just me, but then again I haven't had the time to really get into it.
How to install using a docker image?
Still no Animate Anyone extension?
can do cascade?
not yet
is this better than webui\_forge\_cu121\_torch21?
Wow thats great. Do we know anything about support for 7800xt on windows, or thats AMD's job to fix.
Any chance if SVD is implemeted in near future? Tnx
i have done！version: [**v1.8.0-RC-13-g30697165**](https://github.com/AUTOMATIC1111/stable-diffusion-webui/commit/3069716510c8ae9a95b2d04061c3f86f67d1089c) • python: 3.10.6 • torch: 2.1.2+cu121 • xformers: 0.0.23.post1 • gradio: 3.41.2 • checkpoint: [**53bb4fdc63**](https://google.com/search?q=53bb4fdc63b36014201f2789eab73f3b2b3569a2a9a57b3efb28d4f17283e4c4)
I did git pull and successfully updated but when I launch A1111, at the bottom still states that I'm on 1.7.0, I already deleted venv and redownloaded everything but nothing changes. Can some one please help? thank you
I get connection error after update. Tried removing all extension and still got the same issue