From 9b1d8cfb704d136582cbc3f1bcea267fa2b29653 Mon Sep 17 00:00:00 2001 From: Georg Zoeller Date: Mon, 28 Nov 2022 14:16:29 +0800 Subject: [PATCH] Added Scalable SD Training Signed-off-by: Georg Zoeller --- README.md | 14 ++++++++++---- 1 file changed, 10 insertions(+), 4 deletions(-) diff --git a/README.md b/README.md index 6201761..c39a2ed 100644 --- a/README.md +++ b/README.md @@ -99,14 +99,20 @@ Tools and models for use in conjuction with Stable Diffusion * [Prompt to Prompt](https://github.com/bloc97/CrossAttentionControl) - Unofficial Implementation of Cross-attention-control for prompt to prompt image editing. * [sd-prompt-graph](https://github.com/trevbook/sd-prompt-graph) - This is a React-based curve editor GUI for prompt interpolation animations made with Stable Diffusion. * [DAAM](https://github.com/castorini/daam) - Diffusion attention attribution maps, generating heatmaps modelling the impact of specific terms and tokens in the prompt on the final diffusion result. - -### Customisation -* [Dreambooth-Stable-Diffusion](https://github.com/XavierXiao/Dreambooth-Stable-Diffusion) - Implementation of [Google's DreamBooth](https://arxiv.org/abs/2208.12242) for stable diffusion, allowing fine-tuning of the model for specific concepts. -* [textual-inversion](https://github.com/rinongal/textual_inversion) - Addition of personalized content to Stable Diffusion without retraining the model ([Paper](https://textual-inversion.github.io/), [Paper2](https://dreambooth.github.io/)). * [sd-concepts-library](https://huggingface.co/sd-concepts-library) - A library of user created [textual-inversion](https://textual-inversion.github.io/) embeddings to add new concepts to stable diffusion + +## Training + +* [Dreambooth-Stable-Diffusion](https://github.com/XavierXiao/Dreambooth-Stable-Diffusion) - Implementation of [Google's DreamBooth](https://arxiv.org/abs/2208.12242) for stable diffusion, allowing fine-tuning of the model for specific concepts. + +* [Stable Diffusion Trainer](https://github.com/CCRcmcpe/scal-sdt) - Stable Diffusion trainer with scalable dataset size and hardware usage. Requires 10G of VRAM. + +* [textual-inversion](https://github.com/rinongal/textual_inversion) - Addition of personalized content to Stable Diffusion without retraining the model ([Paper](https://textual-inversion.github.io/), [Paper2](https://dreambooth.github.io/)). + * [Stable Dreamfusion](https://github.com/ashawkey/stable-dreamfusion) - Text to 3D dreamfusion implementation based on stable diffusion. + ### GUIS Most of these GUIS, unless mentioned otherwise in their documentation, include stable-diffusion.