EveryDream2trainer
By victorchall
EveryDream-trainer
General fine tuning for Stable Diffusion (by victorchall)
| EveryDream2trainer | EveryDream-trainer | |
|---|---|---|
| 48 | 32 | |
| 766 | 501 | |
| - | - | |
| 9.0 | 2.4 | |
| 7 days ago | about 1 year ago | |
| Python | Jupyter Notebook | |
| GNU General Public License v3.0 or later | MIT License |
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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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.
EveryDream2trainer
Posts with mentions or reviews of EveryDream2trainer.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-08-04.
- Question on SD Finetuning
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80% Completed!
I'm using EveryDream2 with SD v1 based models. You can define whatever resolution you want for training, as long as your Vram allows it.
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Freedom. Finetuned 2.1 that can gen (+1024x) and often without negative. Release this or next week. Demo available for testing in next days. Here are some creations from a closed beta that I released on Twitter yesterday. 20 people, 3 hours, 1500 gens. I hope you enjoy. More on imgur album.
There is a demo optimizers settings here that uses special settings for the text encoder: https://github.com/victorchall/EveryDream2trainer/blob/main/optimizerSD21.json
- Can we clear up the regularization images concept once and for all?
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Are there any recent, or still relevant, tutorials on training LoRAs within Dreambooth? Any specific / special settings to take advantage of my 4090?
If you have a large dataset of pictures, I'd recommend https://github.com/victorchall/EveryDream2trainer instead of Dreambooth. It has decent documentation (well for an open source project that is) and it has a very nice validation feature (disabled by default) which actually gives you good feedback on how the training is progressing.
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Train a model from 300k images?
EveryDream2 can handle this. They even have tools to help you autocaption using BLIP. https://github.com/victorchall/EveryDream2trainer
- [Dreambooth] The docs for this Dreambooth-like trainer, Everydream2
- Resources for artists interesting in using StableDiffusion as a tool?
- Is Joe Penna's DreamBooth still the best option for training photorealistic persons or faces?
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Can we identify most Stable Diffusion Model issues with just a few circles?
I recoment EveryDream2 for training, it has a lot of nice features. I'm not sure there is a proper manual to learn how to train, but there is a lot of information available. I have been learning this subjects for a few months myself.
EveryDream-trainer
Posts with mentions or reviews of EveryDream-trainer.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-03-10.
- How should I train Dreambooth to understand a new class?
- SDTools v1.5
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Guide on finetuning a model with mid-sized dataset of family pictures
https://github.com/victorchall/EveryDream-trainer Haven't tried it myself.
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I've been collecting millions of images of only public domain /cc0 licensing. I'd like to train a stable diffusion model on the collection. Could some one share their knowledge of what this would take? Otherwise, simply enjoy my library.
In terms of training, you've got some really good links and comments to youtube tutorials, but if you're interested in more information about finetuning a model (as opposed to training from scratch), this is a good repo that has a lot of tools for finetuning, including an auto-captioner using BLIP and automatic file renaming. This is the actual finetuning repo.
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Alternative tools to fine tune stable diffusion models?
Every Dream Trainer: Is basically a Dreambooth combine with Fine Tunning, so you can train multiples thing and a lot images: https://github.com/victorchall/EveryDream-trainer
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Training with Dreambooth Models and/or Training with Automatic 1111 Textural Inversion
If you have the GPU for it, I'd recommend training all three things at once with (for example) https://github.com/victorchall/EveryDream-trainer. It recommends using "ground truth" training images - i.e. images from LAION-5B, which Stable Diffusion was originally trained with to have better prior preservation (retaining the flexibility of the original model) while incorporating new concepts, potentially even several different concepts in a single training run.
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Flexible-Diffusion. My first experiment with finetuning. A broad model with better general aesthetics and coherence for different styles! Scroll for 1.5 vs FlexibleDiffusion grids. (BTW, PublicPrompts.art is back!!!)
I used about 300 captioned images (mainly beautiful MJ stuff), and used https://github.com/victorchall/EveryDream-trainer on RunPod for finetuning
- What do you think is the right dataset size to train/refine on dreambooth?
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Practice your christmas cookies before you bake with this SD 1.5 model
SD 1.5 512x512 model for making christmas style cookies of whatever you'd like. trained on 30 512x512 images with manual captions in everydream
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Guide for train/finetune with different image sizes, not dreambooth
This is the good one: https://github.com/victorchall/EveryDream-trainer
What are some alternatives?
When comparing EveryDream2trainer and EveryDream-trainer you can also consider the following projects:
ComfyUI - The most powerful and modular stable diffusion GUI, api and backend with a graph/nodes interface.
kohya_ss
StableTuner - Finetuning SD in style.
sd-scripts
EveryDream - Advanced fine tuning tools for vision models
stable-diffusion-webui-wd14-tagger - Labeling extension for Automatic1111's Web UI
kohya-trainer - Adapted from https://note.com/kohya_ss/n/nbf7ce8d80f29 for easier cloning
stable-diffusion-webui - Stable Diffusion web UI
fast-stable-diffusion - fast-stable-diffusion + DreamBooth
DreamArtist-stable-diffusion - stable diffusion webui with contrastive prompt tuning
EveryDream2trainer vs ComfyUI
EveryDream-trainer vs kohya_ss
EveryDream2trainer vs StableTuner
EveryDream-trainer vs StableTuner
EveryDream2trainer vs sd-scripts
EveryDream-trainer vs EveryDream
EveryDream2trainer vs stable-diffusion-webui-wd14-tagger
EveryDream-trainer vs kohya-trainer
EveryDream2trainer vs kohya-trainer
EveryDream-trainer vs stable-diffusion-webui
EveryDream2trainer vs fast-stable-diffusion
EveryDream-trainer vs DreamArtist-stable-diffusion