x-stable-diffusion
Real-time inference for Stable Diffusion - 0.88s latency. Covers AITemplate, nvFuser, TensorRT, FlashAttention. Join our Discord communty: https://discord.com/invite/TgHXuSJEk6 (by stochasticai)
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| x-stable-diffusion | sd_dreambooth_extension | |
|---|---|---|
| 5 | 115 | |
| 547 | 1,818 | |
| -0.2% | - | |
| 4.5 | 9.0 | |
| 5 months ago | 27 days ago | |
| Jupyter Notebook | Python | |
| Apache License 2.0 | GNU General Public License v3.0 or later |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
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.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
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.
x-stable-diffusion
Posts with mentions or reviews of x-stable-diffusion.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-11-21.
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[D] Is there an affordable way to host a diffusers Stable Diffusion model publicly on the Internet for "real-time"-inference? (CPU or Serverless GPU?)
Cheapest would be to deploy it on your own using: https://github.com/stochasticai/x-stable-diffusion. Let me if you need more help on real-time inference.
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[D]deploy stable diffusion
However, I suggest you "accelerate" your inference first. For example, you can use open-source inference engines (see: https://github.com/stochasticai/x-stable-diffusion) to easily accelerate your inference 2x or more. That means you can generates 2x more images / $ on public clouds.
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30% Faster than xformers? voltaML vs xformers stable diffusion - NVIDIA 4090
Brilliant, the x-stable-diffusion TensorRT/ AITemplate etc. sample image suggested they weren't consistent between the optimizations at all, unless they hadn't locked the seed which would have been foolish for the test.
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Upto 2.5X speed up of Stable-diffusion/Dreambooth using one line of code with voltaML.
I was looking at this three days ago, the problem is there seems to be a huge difference in what is being generated looking at the example spread on https://github.com/stochasticai/x-stable-diffusion , whereas copying model, params, seed should be giving a near identical image.
- Using Tensor Cores for Deep Learning.
sd_dreambooth_extension
Posts with mentions or reviews of sd_dreambooth_extension.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-07-06.
- SDXL Training for Auto1111 is now Working on a 24GB Card
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(Requesting Help)
I am trying to use StableDiffusion via AUTOMATIC1111 with the Dreambooth extension
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it will be an absolute madness when sdxl becomes standard model and we start getting other models from it
When I first attempted SD training, I was very frustrated. It wasn't until I found this obscure forum thread on Github that I actually started producing great results with Dreambooth. Because I have such satisfactory results, I'm very reluctant to beat my brains against LoRa and its related training techniques. I gave up trying to train TI embeddings a long time ago. And I never figured out how to train or how to use hypernetworks. I've only been able to get good results with Dreambooth directly because of that thread I linked above. I make LoRas by extracting them from Dreambooth-trained checkpoints. And I have no idea if I'm doing the extractions the right way or not.
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"Exception training model: ' Some tensors share memory" with Dreambooth on Vladmatic
Getting the same with automatic1111 and sd_dreambooth extension. Check out more here in the issues log: https://github.com/d8ahazard/sd_dreambooth_extension/issues/1266
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Yo, DreamBooth gatekeepers, SHARE YOUR HYPERPARAMETERS, please.
It's several moths old and many things have changed. But the spreadsheet available through this thread on Github has been indispensable for me when I train Dreambooth models. I'm astounded no one talks about it. I bring it up all the time. The research presented there should be continued. I'd love to see similar research done for SD v2.1.
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What is the BEST solution for hyper realistic person training?
Training rate is paramount. Read this Github thread.
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How do you train your LoRAs, 1 Epoch or >1 Epoch (same # of steps)?
https://github.com/d8ahazard/sd_dreambooth_extension/discussions/547/ (in depth training principles understanding)
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Struggling to install Dreambooth
sd_dreambooth_extension https://github.com/d8ahazard/sd_dreambooth_extension.git main 926ae204 Fri Mar 31 15:12:45 2023 unknown
- Attempting to train a lora with RTX 2060 6 GB vRAM, how to go about this?
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SD just released an open source version of their GUI called StableStudio
also the Dreambooth extension supports API (https://github.com/d8ahazard/sd_dreambooth_extension/blob/main/scripts/api.py) so i'm not sure where do you get those news :/
What are some alternatives?
When comparing x-stable-diffusion and sd_dreambooth_extension you can also consider the following projects:
voltaML - ⚡VoltaML is a lightweight library to convert and run your ML/DL deep learning models in high performance inference runtimes like TensorRT, TorchScript, ONNX and TVM.
lora - Using Low-rank adaptation to quickly fine-tune diffusion models.
AITemplate - AITemplate is a Python framework which renders neural network into high performance CUDA/HIP C++ code. Specialized for FP16 TensorCore (NVIDIA GPU) and MatrixCore (AMD GPU) inference.
kohya_ss
infery-examples - A collection of demo-apps and inference scripts for various deep learning frameworks using infery (Python).
kohya-trainer - Adapted from https://note.com/kohya_ss/n/nbf7ce8d80f29 for easier cloning
jukebox - Code for the paper "Jukebox: A Generative Model for Music"
stable-diffusion-webui-wd14-tagger - Labeling extension for Automatic1111's Web UI
sdui - Local ImGui UI for Stable Diffusion. Features embedded PNG metadata, Apple M1 fixes, result caching, img2img, and more!
dreambooth-training-guide
stable-diffusion-webui - Stable Diffusion web UI
sd-scripts
x-stable-diffusion vs voltaML
sd_dreambooth_extension vs lora
x-stable-diffusion vs AITemplate
sd_dreambooth_extension vs kohya_ss
x-stable-diffusion vs infery-examples
sd_dreambooth_extension vs kohya-trainer
x-stable-diffusion vs jukebox
sd_dreambooth_extension vs stable-diffusion-webui-wd14-tagger
x-stable-diffusion vs sdui
sd_dreambooth_extension vs dreambooth-training-guide
x-stable-diffusion vs stable-diffusion-webui
sd_dreambooth_extension vs sd-scripts