textual_inversion
sd-enable-textual-inversion
| textual_inversion | sd-enable-textual-inversion | |
|---|---|---|
| 30 | 26 | |
| 2,743 | 744 | |
| - | - | |
| 0.8 | 6.5 | |
| about 1 year ago | over 1 year ago | |
| Jupyter Notebook | Python | |
| MIT License | - |
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textual_inversion
- FLiP Stack Weekly for 06 February 2023
- Loading textual inversion embeddings in vanilla SD library?
- Embeddings without using AUTO1111
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How to use embeddings with PyTorch
Checking out https://github.com/rinongal/textual_inversion, which has some possibly informative examples and scripts.
- Textual Inversion
- Advice on Automatic1111 textual inversion tuning?
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Hi. Is training my own textual inversion feasible on one 1070? &how long does it take?
I think currently you will need about 20GB VRam..., options are: 1. https://github.com/rinongal/textual_inversion - localy
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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.
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How close are we to full movie generation from a technical standpoint?
That may mostly solve that but it’s too early right now: https://github.com/rinongal/textual_inversion
For fun I tried to make an entire animated music video but it took over one week of processing and basically fell apart coherently by 30 seconds so just did one third:
https://youtu.be/f3GfUKJBUYA
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Easy Textual Inversion tutorial. How To Train Stable Diffusion With Your Own Art.
The huggingface models don't work with the local stable diffusion, only the models trained locally with this repo https://github.com/rinongal/textual_inversion can be installed, at least for now.
sd-enable-textual-inversion
- Stable Diffusion links from around September 11, 2022 that I collected for further processing
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aiART genertion from an image database.
Yes, what you’re describing can be done using textual inversion.
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Did GoogleAI Just Snooker One of Silicon Valley’s Sharpest Minds?
https://github.com/hlky/sd-enable-textual-inversion
It creates a representation of an entity and allows rending it in different styles and contexts. Currently it involves model fine tuning, but I expect it will become convenient as the power of the operation becomes clear. And once it's convenient, you'll be able to do the progressive queries you're asking for (and it'll be a lot easier to create narratively coherent sets of images.)
- My findings using Textual Inversion for Stable Diffusion
- Question: Does anyone know if it is possible to generate the same image but in different views (like left view, top view, close-up etc) ?
- Could someone make a GUI Textual inversion guide for noobs?
- Useful link
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Teach new concepts to Stable Diffusion with 3-5 images only - and browse a library of learned concepts to use
A branch to add it to SD (which I think the original now has): https://github.com/hlky/sd-enable-textual-inversion
- Further training of stable diffusion
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I don't know anything about python or programming. How can I easily create a .pt file for use with embedding, to generate content based on trained image?
Hey now, there's still an option out there, this Colab notebook, it's able to run on the free tier of Colab. By default, it runs for about 2 hours per embed, and the files made can be used both in the notebook, and on Hlky's front-end, after enabling it, and setting to full precision.
What are some alternatives?
stable-diffusion - A latent text-to-image diffusion model
Dreambooth-Stable-Diffusion - Implementation of Dreambooth (https://arxiv.org/abs/2208.12242) with Stable Diffusion
bitsandbytes - Accessible large language models via k-bit quantization for PyTorch.
stable-diffusion-webui - Stable Diffusion web UI
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-textual-inversion_win
stable-diffusion
stable-diffusion - This version of CompVis/stable-diffusion features an interactive command-line script that combines text2img and img2img functionality in a "dream bot" style interface, a WebGUI, and multiple features and other enhancements. [Moved to: https://github.com/invoke-ai/InvokeAI]
VideoX - VideoX: a collection of video cross-modal models
stable-diffusion-webui - Stable Diffusion web UI [Moved to: https://github.com/Sygil-Dev/sygil-webui]