stable-karlo
automatic
stable-karlo | automatic | |
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10 | 185 | |
62 | 4,745 | |
- | - | |
2.3 | 9.9 | |
about 1 year ago | 6 days ago | |
Python | Python | |
GNU General Public License v3.0 only | GNU Affero General Public License v3.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
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For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
stable-karlo
- Super Easy AI Installer Tool (SEAIT) Update 0.1.0
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Unlimited-Size Diffusion Restoration
This repo uses the SD2 upscaling model in a workflow on top of Karlo and I've run that on my GPU, definitely nothing unusual about the memory requirements: https://github.com/kpthedev/stable-karlo
- [P] stable-karlo - Combining the Karlo diffusion model (based on OpenAI's unCLIP) with Stable-Diffusion v2 upscaling (Local UI + Colab notebook)
- [P] stable-karlo - A UI for Karlo (open-source model based on OpenAI's unCLIP) with Stable-Diffusion v2 upscaling. Google Colab available!
- Diverse examples generated with stable-karlo (link in comments!)
- stable-karlo - A UI for Karlo (open-source model based on OpenAI's unCLIP) with Stable-Diffusion v2 upscaling. Google Colab available!
- [P] Combining Kakaobrain's Karlo text-conditional diffusion model with Stable-Diffusion 2.1 (WebUI)
- I combined Karlo with the Stable Diffusion v2 Upscaler!
automatic
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Open-source project ZLUDA lets CUDA apps run on AMD GPUs
> it won't ever be a viable option
For production workloads, I generally agree. It's an unsupported hack with a questionable future, I wouldn't do anything money-making with it.
However, for tinkering and consumer workloads, it already works pretty well. Enough of cuDNN and cuBLAS work to run PyTorch and in turn, Stable Diffusion with https://github.com/lshqqytiger/ZLUDA - there's even a fairly user-friendly setup process already in https://github.com/vladmandic/automatic .
I was able to get a personal non-ML related project working on my AMD card in just a few minutes, which saved me a lot of development time before I then deployed the production workload on NV hardware (this is probably why AMD pulled the plug on the project - it's almost more of a boost to NV than anything else, AMD really need people to be writing code on ROCm to deploy on AMD datacenter hardware).
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Show HN: Comflowy – A ComfyUI Tutorial for Beginners
While I currently use SD.Next[1], I have tested ComfyUI locally with my AMD card. The UI can be daunting, but you learn quite a great deal about how a Stable Diffusion pipeline works. In addition some innovations and advances find their way into ComfyUI first.
[1] https://github.com/vladmandic/automatic
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Just me or SDXL is bad for rendering trees, grasses, vegetation in general ? Looks a stop motion or unfinished painting. How can I fix it ?
I used SD.NEXT ( https://github.com/vladmandic/automatic ) and https://civitai.com/models/82098/add-more-details-detail-enhancer-tweaker-lora and epicphotogasm_lastUnicorn
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Is SDXL supposed to be this slow on my system?
I found this thread on GitHub talking about how this was fixed in the latest version with an optional setting. I tried enabling it, as they mentioned, but it just resulted in an immediate CUDA out of memory error when starting generation. So it seems I'm actually needing the shared memory, which I assume is my issue.
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Another Monday, another big release from SDNext!
As always, do check out our more detailed changelog, give us a quick install from our Repo, and stop by our Discord Server for any questions or help you may need.
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What's the best stable diffusion client for base m1 MacBook air?
SD.Next
- Intel Arc 770 with Linux Mint, support requested!
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SDNext - Controlnet keeps being disabled after installing SDXL ?
Today I finally wanted to give SDXL a chance, so I set everythin up according to Vladmandic's Wiki https://github.com/vladmandic/automatic/wiki/SD-XL
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Vlad SD.Next SDXL DirectML: 'StableDiffusionXLPipeline' object has no attribute 'alphas_cumprod'
I'm trying to get SDXL working on Vlad's SDNext, but I keep getting the error in the title when trying to run basic operations. I'm not sure what's going on, I followed his guide for it to a T.
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[P] Stable Diffusion XL (SDXL) Benchmark - 769 images per dollar on consumer GPUs
We used an inference container based on SDNext, along with a custom worker written in Typescript that implemented the job processing pipeline. The worker used HTTP to communicate with both the SDNext container and with our batch framework.
What are some alternatives?
stable-diffusion-tensorflow-IntelMetal - Stable Diffusion in TensorFlow / Keras, Designed for Apple Metal on Intel. Forked from @divamgupta's work [Moved to: https://github.com/soten355/MetalDiffusion]
SHARK - SHARK - High Performance Machine Learning Distribution
diffusiondb - A large-scale text-to-image prompt gallery dataset based on Stable Diffusion
stable-diffusion-webui-colab - stable diffusion webui colab
stable-diffusion-videos - Create 🔥 videos with Stable Diffusion by exploring the latent space and morphing between text prompts
kohya_ss
stable-diffusion - Optimized Stable Diffusion able to generate 1088x1088 images on just 4GB GPUs
stable-diffusion-webui-ux - Stable Diffusion web UI UX
alias-free-gan - Unofficial Alias-Free GAN implementation. Based on rosinality's version with expanded training and inference options.
InvokeAI - InvokeAI is a leading creative engine for Stable Diffusion models, empowering professionals, artists, and enthusiasts to generate and create visual media using the latest AI-driven technologies. The solution offers an industry leading WebUI, supports terminal use through a CLI, and serves as the foundation for multiple commercial products.
dream-factory - Multi-threaded GUI manager for mass creation of AI-generated art with support for multiple GPUs.
stable-diffusion-webui-wd14-tagger - Labeling extension for Automatic1111's Web UI