The reason your commands aren't working is that you need to git clone the repository first:
git clone https://github.com/CompVis/stable-diffusion.git
Which will drop a stable-diffusion folder where you ran the command. Once you cd into that directory, you should see an environment.yaml file that you can use for your conda commands:
cd stable-diffusion
conda env create -f ./environment.yaml
If you don't have git installed, you'll want to use a suitable installer from here.
Hi diffusers! Before I was able to run SD in my global enviroment. But I started to work with other projects with different Anaconda enviroments. So I also tried to reinstall SD within Anaconda enviroment with following couple of tutorials. But It didn't work out. The thing is there are very few tutorials about installing it within virtual enviroment and these are kinda outdated. Have you tried to do it? Could you provide me some guidance to install SD using Anaconda?
P.S: I also noticed that I really didn't get the difference between stable-diffusion and stable-diffusion-webui.
Edit: I managed it with this tutorial. There are some slightly differences but the tutorial was helpful. Maybe I could post my own tutorial in sub.
The reason your commands aren't working is that you need to git clone the repository first:
git clone https://github.com/CompVis/stable-diffusion.git
Which will drop a stable-diffusion folder where you ran the command. Once you cd into that directory, you should see an environment.yaml file that you can use for your conda commands:
cd stable-diffusion
conda env create -f ./environment.yaml
If you don't have git installed, you'll want to use a suitable installer from here.
Yes, there are those "easy" options too, such as .exe and .dmg installer files for Windows and Mac's respectively.
There are also some simpler than what you found daunting, but less limited than the above pre-defined, self-contained options, such as via: https://github.com/cmdr2/stable-diffusion-ui
Every option/approach has its trade-offs.
The underlying issue you are contending with is that you are jumping in at the point of 400% - 1,000% yearly AI growth rates and all the rapid changes in evolution and options that this implies, and the desire to bypass the challenge on jumping onto the rapid technology, code and related options that this is. Many of the people, groups and companies powering this amazing revolution and growth rates and sharing this with others also have time constraints, and therefor are fine providing standard modes of setup and access via industry-standard tools and methods like GitHub, Conda, Brew and other such tools. However, a certain percentage of people will be frustrated by this. For them, there are other simplified, less leading-edge access options.
While there are simple installs that are self-contained and relatively easy, they by their nature provide a smaller slice of any given area of AI, which is simplifying for the knowledge/time-constrained individual at the expense of limiting access to many the latest installable or other options.
You can also just use an online version of it where someone has done the more difficult installation and configuration work for you. From Mid Journey and Google Colab options to things you can simply find by searching for online stable diffusion, such as: https://stablediffusionweb.com
Videos
I am doing a new SD install on an pristine new Windows machine and wondering about strategies. Some advise to use Anaconda, I did this on a prior install, but I didn't see any particularutility.
Any opinions about the advantages of managing the install the Anaconda way, rather than just
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Step 1: Install python.
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Step 2: Install git.
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Step 3: Clone web-ui.
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Step 4: Download a model file.
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Step 5: Run webui.
Any reason not to do that, and do the Conda dance?
Recently I have been trying to find ways to get around the "Cuda" problem when generating using control net. I saw a video to download Anaconda and a Cuda 12.2.0. I can now generate photos using control net but now it takes upwards of 20-30 minutes to generate one picture as before, it only took 1-2 minutes. Does Python not work with Anaconda? I am a complete newbie when it comes to this. My command arg. are (--medvram --xformers --no-half --autolaunch)