fast-stable-diffusion
Dreambooth-Stable-Diffusion
fast-stable-diffusion | Dreambooth-Stable-Diffusion | |
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239 | 100 | |
7,316 | 3,166 | |
- | - | |
8.6 | 6.8 | |
20 days ago | 4 months ago | |
Python | Jupyter Notebook | |
MIT License | MIT License |
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fast-stable-diffusion
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Working Colab notebooks for training Dreambooth?
I tried using TheLastBen's fast dreambooth trainer. I managed to train a ckpt file but I can't run it.
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Running AUTOMATIC1111 on Google Colab
You have a colab from ThelastBen It uses to be thes best at the time when auto1111 was working in google colab free. https://github.com/TheLastBen/fast-stable-diffusion
- Stability AI releases its latest image-generating model, Stable Diffusion XL 1.0
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Google Colab disconnects after 5 mins of hosting A1111
Using https://github.com/TheLastBen/fast-stable-diffusion
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I'm kinda new to all of this and just wanted to ask... How can I fix something like this? Tried inpaint but didn't work even after changing parameters and img2img make it lose quality...
This repo offers a template how to start with SD on runpod https://github.com/TheLastBen/fast-stable-diffusion. But I know how to code, si I made my own solution.
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Unable to use ControlNet on AUTO1111 GUI - Google Colab Notebook
I can confirm I'm using the latest version of the colab notebook of this repo (https://github.com/TheLastBen/fast-stable-diffusion). Anyone can point to any solutions to this problem? Thanks in advance!
- Automatic 1111 not working
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Useful Links
TheLastBen's Fast DB SD Colabs, +25-50% speed increase, AUTOMATIC1111 + DreamBooth
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Can you use other base model to train your own model with TheLastBen or ShivamShrirao collab?
CalledProcessError Traceback (most recent call last) in () 182 wget.download('https://github.com/TheLastBen/fast-stable-diffusion/raw/main/Dreambooth/det.py') 183 print('Detecting model version...') --> 184 Custom_Model_Version=check_output('python det.py '+sftnsr+' --MODEL_PATH '+MODEL_PATH, shell=True).decode('utf-8').replace('\n', '') 185 clear_output() 186 print(''+Custom_Model_Version+' Detected')
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How to Install and Run Stable Diffusion in Automatic1111 with Deforum in Google Collab?
have you tried https://github.com/TheLastBen/fast-stable-diffusion ?
Dreambooth-Stable-Diffusion
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Will there be comprehensive tutorials for fine-tuning SD XL when it comes out?
Tons of stuff here, no? https://github.com/JoePenna/Dreambooth-Stable-Diffusion/
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Useful Links
Joe Penna's Dreambooth (Tutorial|24GB) Most popular DB repo with great results.
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Dreambooth / Custom Training / Model - what's the state of the art?
1) The https://github.com/JoePenna/Dreambooth-Stable-Diffusion instructions say to use the 1.5 checkpoints - is that the latest? Can I use the 2+ models or?
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My Experience with Training Real-Person Models: A Summary
I quickly turned to the second library, https://github.com/JoePenna/Dreambooth-Stable-Diffusion, because its readme was very encouraging, and its results were the best. Unfortunately, to use it on Colab, you need to sign up for Colab Pro to use advanced GPUs (at least 24GB of VRAM), and training a model requires at least 14 compute units. As a poor Chinese person, I could only buy Colab Pro from a proxy. The results from JoePenna/Dreambooth-Stable-Diffusion were fantastic, and the preparation was straightforward, requiring only <=20 512*512 photos without writing captions. I used it to create many beautiful photos.
- I Used Stable Diffusion and Dreambooth to Create an Art Portrait of My Dog
- training
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Training a model on Iwanaga Kotoko (from in/spectre), which step do you guys think the model is at its best?
I've found EveryDream to be brilliant and have switched from JoePenna's Dreambooth because I've found I get better results so long as I provide good captions for all the images, even if preparing the dataset takes 3x as long (took me 2 hours to crop and label the 54 images).
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Dreambooth training results for face, object and style datasets with various prior regularization settings.
From what I know you can train with whatever size you want. But you need software that will support it. For example, ShivamShrirao/diffusers repo seems to allow a change of dimension. Also, you need HW that would support the training, because bigger images need more VRAM, for example,Joe Penna repo is using ~23GB with 512x512px so probably it's not a valid option. But the ShivamShrirao repo has optimizations that allow to run it with less VRAM.
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Starting to get quite good results with Dreambooth. What do you think? (Follow @RokStrnisa on Twitter for more.)
This is a good starting place: https://github.com/JoePenna/Dreambooth-Stable-Diffusion
- I'm a N00b with training stuff. Trying to get runpod with Dreambooth training some images (80 total) and I'm getting this error. Help?
What are some alternatives?
DeepFaceLab - DeepFaceLab is the leading software for creating deepfakes.
Dreambooth-SD-optimized - Implementation of Dreambooth (https://arxiv.org/abs/2208.12242) with Stable Diffusion
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.
Stable-Diffusion-Regularization-Images - For use with fine-tuning, especially the current implementation of "Dreambooth".
stable-diffusion-tensorflow - Stable Diffusion in TensorFlow / Keras
A1111-Web-UI-Installer - Complete installer for Automatic1111's infamous Stable Diffusion WebUI
efficient-dreambooth - [Moved to: https://github.com/smy20011/dreambooth-docker]
civitai - A repository of models, textual inversions, and more
stable-diffusion-webui-docker - Easy Docker setup for Stable Diffusion with user-friendly UI
stable-diffusion-webui - Stable Diffusion web UI [Moved to: https://github.com/Sygil-Dev/sygil-webui]
stable-diffusion - A latent text-to-image diffusion model