fast_Dreambooth_4_kaggle
a version of fast_Dreambooth by TheLastBen for kaggle notebook (by tuwonga)
dreambooth-training-guide
By nitrosocke
fast_Dreambooth_4_kaggle | dreambooth-training-guide | |
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4 | 30 | |
17 | 595 | |
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5.2 | 10.0 | |
12 months ago | over 1 year ago | |
Jupyter Notebook | ||
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The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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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.
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.
fast_Dreambooth_4_kaggle
Posts with mentions or reviews of fast_Dreambooth_4_kaggle.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-11-05.
dreambooth-training-guide
Posts with mentions or reviews of dreambooth-training-guide.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-05-13.
- [Sdforall] L'extension Dreambooth pour Automatic111 est sortie
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Creating own model like the ones on civitai.com
I dont have the time right now, but the rule of thumb for me was 80 unet learning steps for 1 image. Atleast 40 regularization images. Read more about regularization images here: https://github.com/nitrosocke/dreambooth-training-guide
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Image background for LORA training images
This tutorial for dreambooth training has advice with regard to backgrounds which is probably also applicable to LORA. It recommends including images with solid, non-transparent backgrounds but not using them exclusively. Images that focus on the torso and face are probably most important unless your subject has very distinctive legs and feet. Removing other subjects is a must if you're training for a specific subject.
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Non-technical tips for ideal training of Stable Diffusion through Dreambooth?
I found this, I'm going to go through this guide. Seems like I am using far too many images. https://github.com/nitrosocke/dreambooth-training-guide
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Questions about Regularization Images to be used in Dreambooth
Nitrosocke's guide already tells how much and what kind of images to use.
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What’s going to be a problem 20 years from now that people are choosing to ignore?
Dreambooth lets you do it in less than 100 images. https://github.com/nitrosocke/dreambooth-training-guide These folks say it's 5-15 to train on a person but I've not tested myself. https://www.reddit.com/r/StableDiffusion/comments/10tqy88/were\_launching\_a\_lightningfast\_dreambooth\_service/
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We’re launching a lightning-fast Dreambooth service: finetune 1’500 steps in 5min!
See eg this tutorial for styles: https://github.com/nitrosocke/dreambooth-training-guide
- Would it be possible to pretrain generation to mimic my art style?
- Dreambooth model training : dataset labelling
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Introducing Macro Diffusion - A model fine-tuned on over 700 macro images (Link in the comments)
The first time I tried to Dreambooth a style it went poorly. Then I found Nitrosocke's Dreambooth Training Guide and realized my problems were caused by a poorly redacted dataset.
What are some alternatives?
When comparing fast_Dreambooth_4_kaggle and dreambooth-training-guide you can also consider the following projects:
dreambooth-gui
sd_dreambooth_extension
dreambooth-docker
StableTuner - Finetuning SD in style.
stable-diffusion-webui - Stable Diffusion web UI
diffusers - 🤗 Diffusers: State-of-the-art diffusion models for image and audio generation in PyTorch
stablediffusion - High-Resolution Image Synthesis with Latent Diffusion Models
DiffusionToolkit - Metadata-indexer and Viewer for AI-generated images
stable-diffusion-webui - Stable Diffusion web UI
Dreambooth-Stable-Diffusion - Implementation of Dreambooth (https://arxiv.org/abs/2208.12242) by way of Textual Inversion (https://arxiv.org/abs/2208.01618) for Stable Diffusion (https://arxiv.org/abs/2112.10752). Tweaks focused on training faces, objects, and styles.
fast_Dreambooth_4_kaggle vs dreambooth-gui
dreambooth-training-guide vs sd_dreambooth_extension
fast_Dreambooth_4_kaggle vs dreambooth-docker
dreambooth-training-guide vs StableTuner
dreambooth-training-guide vs stable-diffusion-webui
dreambooth-training-guide vs dreambooth-gui
dreambooth-training-guide vs diffusers
dreambooth-training-guide vs stablediffusion
dreambooth-training-guide vs DiffusionToolkit
dreambooth-training-guide vs dreambooth-docker
dreambooth-training-guide vs stable-diffusion-webui
dreambooth-training-guide vs Dreambooth-Stable-Diffusion