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The original was posted on /r/stablediffusion by /u/Excellent_Set_1249 on 2024-10-14 07:51:24+00:00.

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The original was posted on /r/stablediffusion by /u/cgpixel23 on 2024-10-14 06:43:51+00:00.

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The original was posted on /r/stablediffusion by /u/3deal on 2024-10-14 00:52:48+00:00.

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The original was posted on /r/stablediffusion by /u/Numzoner on 2024-10-13 23:02:58+00:00.

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The original was posted on /r/stablediffusion by /u/renderartist on 2024-10-13 22:15:37+00:00.

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The original was posted on /r/stablediffusion by /u/Estylon-KBW on 2024-10-13 17:17:53+00:00.

What I did was basically this, not really rocket science. I've generated a character sheet with flux with a full body, 2 close portraits and a back view. I trained a lora on flux with Ai toolkit in that single image for 500 steps. After that I generated 20 images in different poses setting of the character and I trained another lora with 2000 steps. Both were caption tagged with joy caption tagger. Works like a charm, I tried even on OC drawn by artists that have a single image and even weirder one produce good results. Flux is quite incredibile honestly.

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The original was posted on /r/stablediffusion by /u/simpleuserhere on 2024-10-13 13:51:57+00:00.

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The original was posted on /r/stablediffusion by /u/RenoHadreas on 2024-10-13 18:51:21+00:00.

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The original was posted on /r/stablediffusion by /u/Robo420- on 2024-10-13 15:44:25+00:00.

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The original was posted on /r/stablediffusion by /u/jmellin on 2024-10-13 13:59:40+00:00.

Hey everyone!

I'm excited to share the launch of CogVideoX-LoRAs, a dedicated GitHub repository that serves as a central hub for all LoRA (Low-Rank Adaptation) models created for CogVideoX.

With the rise of community-based fine-tuned weights for CogVideoX, I quickly realized that it would be challenging to find all these new models being created. The need for a unified place to collect and share LoRA models tailored for CogVideoX was evident. With the growing demand for customized video generation, I wanted to create a space where users, developers, and researchers can easily access, contribute to, and collaborate on various LoRA models.

What you can find

• (To-be) Comprehensive Collection: A growing list of all available LoRAs with direct links to their Hugging Face repositories.
• Community Contributions: An open invitation for everyone to contribute their models or improvements, fostering a collaborative environment.
• Easy Navigation: Clear organization and categorization of LoRA models to make discovery and usage straightforward.

What's to come

• Usage Examples: Code snippets and documentation to help you get started quickly with the models.
• Training Examples: Code snippets and documentation to assist you in training your own weights based on your hardware and environment.

Check it out!

You can explore the repository here: CogVideoX-LoRAs GitHub Repo

List of currently available LoRAs is found here: LoRA Models

I welcome any feedback, suggestions, or contributions! If you have a LoRA model you'd like to add or any ideas for improvement, feel free to open a pull request or leave a comment. Let's build a robust collection together!

Thanks for your interest, and I look forward to seeing the amazing LoRAs you all create! 🚀

Update:

Added a python script to simplify contributing to the list and keep a structured table without the need for manual edit. The script asks for two inputs.

• HF-link to the repository
• Short description of lora, not more than 250 characters.

Fork the repo, run python file and create a PR - Done!

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The original was posted on /r/stablediffusion by /u/mcmonkey4eva on 2024-10-13 11:09:30+00:00.

Been a couple months since the last version release, was busy with work on ComfyUI and a surprise trip to Tokyo, but I'm back in full force now. These features were all added in dev versions across the past 2 months, so those already running Swarm will already be used to some of this.

Main new features:

• GGUF Support for Flux models (see docs @ )

• Helper utility for bulk civitai sourced metadata updates, for those collecting models and not using the downloader utility that autoimports civitai metadata

Also, civitai itself supports SwarmUI generated image metadata and lists Swarm as a known tool now!

• Weebs rejoice! Feature requests related to autcompletions have all been handled, and there's a whole bunch of settings to configure it all the different weird ways booru users in particular demand

• New Extensions manager tab under Server, so you can easily install and manage the SwarmUI extensions that are starting to appear! Also I've added a bunch of code internal upgrades designed specifically to make it easier to develop extensions

• Swarm now builds as an executable, rather than using 'dotnet' to launch the process. Everything behaves the same, and the old .dll launch works if you have custom scripts, just Swarm is uniquely identified in task manager and has an exe icon and stuff like that now. This might make Windows do that Do you want to let this app access the network? popup thing.

See the rest of what changed in the release notes here: (I have over 30 lines of noteworthy main features listed here, and there's over 200 commits since the last release!)

Or join the Discord at and watch the #announcements channel to see new things earlier

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The original was posted on /r/stablediffusion by /u/Designer-Pair5773 on 2024-10-13 12:21:11+00:00.

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The original was posted on /r/stablediffusion by /u/Total-Resort-3120 on 2024-10-13 09:25:18+00:00.

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The original was posted on /r/stablediffusion by /u/terminusresearchorg on 2024-10-13 04:43:18+00:00.

the release:

New to this release include goodies like loss masking (as in OneTrainer or Kohya's tools) and a new regularisation technique described in the Dreambooth guide that achieves something like this.

• no lora = the base Flux model
• no_reg = typical Flux LoRA training
• prior_reg_self = setting the training data as is_regularisation_data=true
• prior_reg_ext = externally-obtained regularisation images (but not super high quality)

this is the recommended method ^

• prior_reg_self-empty = no captions on the training data, being used as the regularisation dataset

provided by dxqbYD

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The original was posted on /r/stablediffusion by /u/eggs-benedryl on 2024-10-13 01:45:57+00:00.

I think this is a huge barrier going back to comfy or giving it much thought. It feels like there ought to be a solution to this that isn't keeping a pen and paper notebook full of models and triggers.

I've seen people set up multi node processes to view tagging data but that isn't a very intuitive or easy solution, adding more nodes to a workflow never feels like the best solution.

Is there an extension i'm not aware of? Hopefully in the sea of custom nodes someone's solved this problem by now?

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The original was posted on /r/stablediffusion by /u/pheonis2 on 2024-10-13 03:08:41+00:00.

A new state-of-the-art open-source model, F5-TTS, was released just a few days ago! This cutting-edge model, boasting 335M parameters, is designed for English and Chinese speech synthesis. It was trained on an extensive dataset of 95,000 hours, utilizing 8 A100 GPUs over the course of more than a week.

HF Space:

Github:

Demo: https://swivid.github.io/F5-TTS/

Weights: https://huggingface.co/SWivid/F5-TTS

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The original was posted on /r/stablediffusion by /u/Robo420- on 2024-10-12 15:21:45+00:00.

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The original was posted on /r/stablediffusion by /u/crystal_alpine on 2024-10-12 23:26:22+00:00.

Hi, r/StableDiffusion. We want to flag an impersonator group named comfy-ui DOT org. (Avoid driving traffic to their site; screenshots are included below.) We are NOT affiliated with this site and organization. They set up the site and a Patreon page and even listed Comfy Org teams under their team page. They do include the non-affiliation claim at places but seem to target people who are unaware of funding their Patreon.

Comfy-Ui Dot Org Home page

Patreon is listed under an account called monolab

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The original was posted on /r/stablediffusion by /u/Angrypenguinpng on 2024-10-12 18:37:25+00:00.

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The original was posted on /r/stablediffusion by /u/AdHominemMeansULost on 2024-10-12 18:56:33+00:00.

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The original was posted on /r/stablediffusion by /u/rerri on 2024-10-12 14:50:07+00:00.

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The original was posted on /r/stablediffusion by /u/jenza1 on 2024-10-12 11:55:42+00:00.

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The original was posted on /r/stablediffusion by /u/BillMeeks on 2024-10-12 11:19:50+00:00.

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The original was posted on /r/stablediffusion by /u/CeFurkan on 2024-10-12 14:36:37+00:00.

Triton package is the source of all slowness we have on Windows, e.g. we can't torch.compile because of Triton >

All other packages fully supporting Windows except Triton (developed by OpenAI) like DeepSpeed, Accelerate, TensorRT, ONNX, Bitsandbytes, xFormers, even Pytorch and such

Now there are also some libraries that wants to support Windows but they are depended on Triton, thus they are not able to support Windows

So what you can do? You can reply to this GitHub pull request which community wanted to support Triton on Windows but OpenAI's team rejected :

And the funny thing is that OpenAI is getting 10s of billions of $$$ from Microsoft

At every chance I complain but I don't see such same demand from community

Here also checkout this post for Fast FLUX :

By the way here we are replying against OpenAI (valued 100s of billions of dollars) not individual fun time Open Source developers

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The original was posted on /r/stablediffusion by /u/oodelay on 2024-10-12 13:35:54+00:00.