sd-disable-textual-inversion
Copy these files to your stable-diffusion to disabled text-inversion (by hlky)
| Stable-textual-inversion_win | sd-disable-textual-inversion | |
|---|---|---|
| 15 | 1 | |
| 240 | 3 | |
| - | - | |
| 10.0 | 10.0 | |
| over 1 year ago | over 1 year ago | |
| Jupyter Notebook | Python | |
| MIT License | - |
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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.
Stable-textual-inversion_win
Posts with mentions or reviews of Stable-textual-inversion_win.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-09-26.
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Using DreamBooth on SD on a 3090 w/24gb VRAM (about 1.5 hrs to train)
Would it be possible for you to add this new code in the "regular" textual inversion code? like in this one : https://github.com/nicolai256/Stable-textual-inversion_win - I'm using a 3090, batch size of 3, workers 10, size 384 - works pretty good but if your modification could reduce the VRAM, it could go faster.
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Question About Running Local Textual Inversion
Rinongal and nicolai256 versions, the latter of which is also the one explained in Nerdy Rodent's youtube video https://www.youtube.com/watch?v=WsDykBTjo20, work but they also have an issue of lacking editability in comparison to one made by huggingface's collab which is followed up in a very long issue on Rinongal's Github. You can add accumulate_grad_batches: 4 to the end of the finetune files like shown in Nerdy Rodent's video at this time stamp to try to alleviate this issue, but the quality isn't as good as one made in the online collab.
- NMKD Stable Diffusion GUI 1.4.0 is here! Now with support for inpainting, HuggingFace concepts, VRAM optimizations, and the model no longer needs to be reloaded for every prompt. Full changelog in comments!
- Useful link
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I like Disco Elysium so have been trying some Textual Inversion training + some internal prompt business to replicate the look of the portraits.
the prompt for this one was "a portrait of beautiful young \, painting by Michael Garmash and Kilian Eng, in the style of &",* after training * with pictures of my GF and & with all the Disco Elysium portrait pictures. using the stuff here: https://github.com/nicolai256/Stable-textual-inversion_win, also, thank you u/ExponentialCookie.
- My Stable Diffusion GUI update 1.3.0 is out now! Includes optimizedSD code, upscaling and face restoration, seamless mode, and a ton of fixes!
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Textual Inversion Help
Here is an alternate fork of the repo you talked about: https://github.com/nicolai256/Stable-textual-inversion_win
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Is there any info on how to finetune without using textual inversion?
From my understanding the only finetuning people are doing currently is using textual inversion (this https://github.com/nicolai256/Stable-textual-inversion_win/ and this https://www.reddit.com/r/StableDiffusion/comments/wvzr7s/tutorial_fine_tuning_stable_diffusion_using_only/), but this seems very different from the real finetuning Emad was talking about, and what others (like NovelAI) are doing?
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A user did an Arvalis / RJ Palmer fine-tune (textual inversion)
Cred. to florishdiffusion for showing these gens. I'm not knowledgeable on how to use text inversion but it is possible to do in Free Colab from this source
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Self Portrait, using SD and textual inversion trained on images of myself
what is your --init_word? also what is your prompt for generation? i have doing person training for 6 day and not getting a good results damn! i use https://github.com/nicolai256/Stable-textual-inversion_win
sd-disable-textual-inversion
Posts with mentions or reviews of sd-disable-textual-inversion.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-09-07.
What are some alternatives?
When comparing Stable-textual-inversion_win and sd-disable-textual-inversion you can also consider the following projects:
stable-diffusion
textual_inversion
sd-enable-textual-inversion - Copy these files to your stable-diffusion to enable text-inversion
stable-diffusion - A latent text-to-image diffusion model
bitsandbytes - Accessible large language models via k-bit quantization for PyTorch.
stylegan2-projecting-images - Projecting images to latent space with StyleGAN2.
stable-diffusion
text2image-gui - Somewhat modular text2image GUI, initially just for Stable Diffusion
text2image-gui - Somewhat modular text2image GUI, initially just for Stable Diffusion
stable-diffusion
Stable-textual-inversion_win vs stable-diffusion
sd-disable-textual-inversion vs textual_inversion
Stable-textual-inversion_win vs textual_inversion
sd-disable-textual-inversion vs sd-enable-textual-inversion
Stable-textual-inversion_win vs stable-diffusion
Stable-textual-inversion_win vs sd-enable-textual-inversion
Stable-textual-inversion_win vs bitsandbytes
Stable-textual-inversion_win vs stylegan2-projecting-images
Stable-textual-inversion_win vs stable-diffusion
Stable-textual-inversion_win vs text2image-gui
Stable-textual-inversion_win vs text2image-gui
Stable-textual-inversion_win vs stable-diffusion