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. (by VoltaML)
| voltaML | sd_dreambooth_extension | |
|---|---|---|
| 5 | 115 | |
| 1,184 | 1,824 | |
| 0.0% | - | |
| 10.0 | 8.7 | |
| over 1 year ago | about 1 month ago | |
| Python | 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.
voltaML
Posts with mentions or reviews of voltaML.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-11-21.
- Very first testing version of voltaML is out (giant speed increase)
- VoltaML – convert DL models in high performance inference runtimes
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[R] Upto 2.5X speed up of Stable-diffusion/Dreambooth using one line of code with voltaML.
Please follow here-> https://github.com/VoltaML/voltaML
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Upto 2.5X speed up of Stable-diffusion/Dreambooth using one line of code with voltaML.
Follow us here to get updates on the SD acceleration -> https://github.com/VoltaML/voltaML
- [R] Open source inference acceleration library - voltaML
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 voltaML and sd_dreambooth_extension you can also consider the following projects:
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.
lora - Using Low-rank adaptation to quickly fine-tune diffusion models.
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
kohya_ss
jukebox - Code for the paper "Jukebox: A Generative Model for Music"
kohya-trainer - Adapted from https://note.com/kohya_ss/n/nbf7ce8d80f29 for easier cloning
stable-diffusion-webui - Stable Diffusion web UI
stable-diffusion-webui-wd14-tagger - Labeling extension for Automatic1111's Web UI
dreambooth-training-guide
sd-scripts
sd-webui-controlnet - WebUI extension for ControlNet
stable-diffusion-ncnn-vulkan
voltaML vs AITemplate
sd_dreambooth_extension vs lora
voltaML vs x-stable-diffusion
sd_dreambooth_extension vs kohya_ss
voltaML vs jukebox
sd_dreambooth_extension vs kohya-trainer
voltaML vs stable-diffusion-webui
sd_dreambooth_extension vs stable-diffusion-webui-wd14-tagger
sd_dreambooth_extension vs dreambooth-training-guide
sd_dreambooth_extension vs sd-scripts
sd_dreambooth_extension vs sd-webui-controlnet
sd_dreambooth_extension vs stable-diffusion-ncnn-vulkan