LoRA-EXTRACTOR
stable-diffusion-webui
LoRA-EXTRACTOR | stable-diffusion-webui | |
---|---|---|
8 | 2,808 | |
73 | 130,470 | |
- | - | |
10.0 | 9.9 | |
about 1 year ago | 1 day ago | |
Python | Python | |
- | MIT |
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LoRA-EXTRACTOR
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The duality of this subreddit
Regardless of the method used to fine tune the model it wouldn't exceed the sizes I listed above. (fun fact, the maximum dimensions for LoRA is 320 (which limits the LoRA models to ~500mb, because that is the size of the smallest tensor) https://github.com/sashaok123/LoRA-EXTRACTOR/issues/8 (with LoCons it might be slightly larger, but I have not check out the theoretical limit of LoCons yet)
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LORA Extraction from Custom Models in Google Colab
I changed sashaok123's code to work on Google Colab. https://github.com/AlirezaF80/LoRA-EXTRACTOR-Colab
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Lora extractions VS. DB model - Can we truly replace 2/4gb models with 300mb Loras for the same results?
Can you extract a "LoRA transform" by comparing the weights from 2 checkpoints? Yes you can. https://github.com/sashaok123/LoRA-EXTRACTOR/blob/main/lib/extract_lora_from_models.py is a script that does exactly that, and if you look at the code, all it is is just applying singular value decomposition (SVD) (the underlying method behind principal component analysis (PCA), for those who are more Statistics/ML minded) to calculate the transformation between the two. Will you lose information when you "compress" the network using SVD? yes, the amount of "information" (in stats this is measured by variance) explained by the "lower ranked" component omitted by the new compressed representation, however the more similar the networks are, the less components will be needed to represent the differences.
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Automatic1111 Webui Help: Dreambooth + DeepSpeed LoRA Training on 8GB VRAM
Instead of using kohya_ss, I used https://github.com/sashaok123/LoRA-EXTRACTOR
- LORA extractor tool
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Can someone request AUTO1111 to include LORA-extraction script by sashaok123?
Here is the link to the LORA-extraction script on github by sashaok123: https://github.com/sashaok123/LoRA-EXTRACTOR
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Created a tiny script for more convenient extraction of LoRA models
Link to GitHub, where you can download the script.
stable-diffusion-webui
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Show HN: I made an app to use local AI as daily driver
* LLaVA model: I'll add more documentation. You are right Llava could not generate images. For image generation I don't have immediate plans, but checkout these projects for local image generation.
- https://diffusionbee.com/
- https://github.com/comfyanonymous/ComfyUI
- https://github.com/AUTOMATIC1111/stable-diffusion-webui
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AMD Funded a Drop-In CUDA Implementation Built on ROCm: It's Open-Source
I would love to be able to have a native stable diffusion experience, my rx 580 takes 30s to generate a single image. But it does work after following https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki...
I got this up and running on my windows machine in short order and I don't even know what stable diffusion is.
But again, it would be nice to have first class support to locally participate in the fun.
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Ask HN: What is the state of the art in AI photo enhancement?
In Auto1111, that just uses Image.blend. :)
https://github.com/AUTOMATIC1111/stable-diffusion-webui/blob...
- How To Increase Performance Time on MacOS
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Can anyone suggest an AI model that can help me enhance a poorly drawn logo?
I used SDXL in automatic1111 webui for both images. Now that I think about it, the procedure I described was how I made this one, but the one that looks like an illustration was done in two steps. I used the canny ControlNet as I said for the outer part of the logo to preserve the shape of the fonts, but I had to turn it off for the boot to give SDXL leeway to add detail and make it look more like a boot.
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Seeking out an experienced and empathetic coding buddy.
That said, please do learn coding and don't get discouraged when somebody says to learn PyTorch or recommends using a Jupiter notebook with no further information on how to translate the skill into images. I would highly recommend some short term goals. Get your feet wet by taking apart the UIs. The comfy API documentation is here and the A1111 API documentation is here. There is a difference in completeness, welcome to programming. Writing nodes or plugins is also a good way to jump into this world. Custom wildcard logic might be very attractive to you if you aren't the type that want to deal with a nested file structure to simulate logic.
- can't get it working with an AMD gpu
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SD extension that allows for setting override
Possibly Unprompted? https://github.com/AUTOMATIC1111/stable-diffusion-webui/discussions/8094
- Need to write an application to use Stable Diffusion on my desktop PC - which resource should I learn to use?
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4090 Speed Decrease on each Generation/Iteration
version: v1.6.1 • python: 3.10.13 • torch: 2.0.1+cu118 • xformers: 0.0.20 • gradio: 3.41.2 • checkpoint: 6e8d4871f8
What are some alternatives?
LoRA-EXTRACTOR-Colab - A small script to extract LoRA models from custom checkpoints, in Google Colab.
stable-diffusion-ui - Easiest 1-click way to install and use Stable Diffusion on your computer. Provides a browser UI for generating images from text prompts and images. Just enter your text prompt, and see the generated image. [Moved to: https://github.com/easydiffusion/easydiffusion]
sd-scripts
ComfyUI - The most powerful and modular stable diffusion GUI, api and backend with a graph/nodes interface.
kohya_ss
SHARK - SHARK - High Performance Machine Learning Distribution
lora - Using Low-rank adaptation to quickly fine-tune diffusion models.
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.
safetensors - Simple, safe way to store and distribute tensors
diffusers - 🤗 Diffusers: State-of-the-art diffusion models for image and audio generation in PyTorch and FLAX.
sd-webui-additional-networks
CodeFormer - [NeurIPS 2022] Towards Robust Blind Face Restoration with Codebook Lookup Transformer