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Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Lora beYond Conventional methods, Other Rank adaptation Implementations for Stable diffusion.
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| 2026-07-24 | 2503 |
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Today
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This week
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Momentum
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      # LyCORIS - Lora beYond Conventional methods, Other Rank adaptation Implementations for Stable diffusion. (ICLR'24)  A project that implements different parameter-efficient fine-tuning algorithms for Stable Diffusion. This project originated from LoCon (see archive branch). **If you are interested in discussing more details, you can join [our Discord server](https://discord.gg/VtTFKrj9gJ)** [](https://discord.gg/VtTFKrj9gJ) **If you want to check more in-depth experiment results and discussions for LyCORIS, you can check our [paper](https://openreview.net/forum?id=wfzXa8e783)** **Documentation starts at [docs/README.md](docs/README.md)** — it maps every document and source folder to the question it answers. ## Algorithm Overview LyCORIS currently contains LoRA (LoCon), LoHa, LoKr, (IA)^3, DyLoRA, Native fine-tuning (aka dreambooth). GLoRA and GLoKr are coming soon. Please check [List of Implemented Algorithms](docs/algorithms/README.md) and [Guidelines](docs/algorithms/guidelines.md) for more details. A simple comparison of some of these methods are provided below (to be taken with a grain of salt) | | Full | LoRA | LoHa | LoKr low factor | LoKr high factor $^+$ | | --------------------- | ---- | ---- | ---- | --------------- | ---------------------- | | Fidelity | ★ | ● | ▲ | ◉ | ▲ | | Flexibility $^*$ | ★ | ● | ◉ | ▲ | ● $^†$ | | Diversity | ▲ | ◉ | ★ | ● | ★ | | Size | ▲ | ● | ● | ● | ★ | | Training Speed Linear | ★ | ● | ● | ★ | ★ | | Training Speed Conv | ● | ★ | ▲ | ● | ● | ★ > ◉ > ● > ▲ [> means better and smaller size is better] $^+$ Usually we take `factor <= 0.5 * sqrt(dim)` as low factor and `factor >= sqrt(dim` as high factor. For example, factor<=8 for SD1.x/SD2.x/SDXL can be seen as low factor, and, factor>=16 can be seen as high factor. <br> $^*$ Flexibility means anything related to generating images not similar to those in the training set, and combination of multiple concepts, whether they are trained together or not <br> $^†$ It may become more difficult to switch base model or combine multiple concepts in this situation <br> **The actual performance may vary depending on the datasets, tasks, and hyperparameters used. It is recommended to experiment with different settings to achieve optimal results.** ## Usage ### Image Generation #### [a1111/sd-webui](https://github.com/AUTOMATIC1111/stable-diffusion-webui) After sd-webui 1.5.0, LyCORIS models are officially supported by the built-in LoRA system. You can put them in either `models/Lora` or `models/LyCORIS` and use the default syntax `<lora:filename:multiplier>` to trigger it. When we add new model types, we will always make sure they can be used with the newest version of sd-webui. As for sd-webui with version < 1.5.0 or sd-webui-forge, please check this [extension](https://github.com/KohakuBlueleaf/a1111-sd-webui-lycoris). #### Others As far as we are aware, LyCORIS models are also supported in the following interfaces / online generation services (please help us complete the list!) - [ComfyUI](https://github.com/comfyanonymous/ComfyUI) - [InvokeAI](https://github.com/invoke-ai/InvokeAI) - [CivitAI](https://civitai.com/) - [Tensor.Art](https://tensor.art/) However, newe
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Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:788f79c98d499410, topic:stable-diffusion, readme:image generation, desc:stable diffusion
matched fp:788f79c98d499410, readme:fine-tuning, readme:fine tuning, desc:lora