File:Demonstration of DreamBooth AI model fine-tuning for Stable Diffusion using Jimmy Wales training data from Wikimedia Commons.png
![File:Demonstration of DreamBooth AI model fine-tuning for Stable Diffusion using Jimmy Wales training data from Wikimedia Commons.png](https://upload.wikimedia.org/wikipedia/commons/thumb/e/e5/Demonstration_of_DreamBooth_AI_model_fine-tuning_for_Stable_Diffusion_using_Jimmy_Wales_training_data_from_Wikimedia_Commons.png/675px-Demonstration_of_DreamBooth_AI_model_fine-tuning_for_Stable_Diffusion_using_Jimmy_Wales_training_data_from_Wikimedia_Commons.png?20230808103502)
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摘要
[编辑]描述Demonstration of DreamBooth AI model fine-tuning for Stable Diffusion using Jimmy Wales training data from Wikimedia Commons.png |
Demonstration of the use of DreamBooth to fine-tune a text-to-image diffusion model (in this particular case, Stable Diffusion) so that it can algorithmically generate highly specialised and customised image outputs. This demonstration features six output images of Jimmy Wales, founder of Wikipedia, performing bench press exercises at a fitness gym.
The model checkpoint was fine-tuned in DreamBooth using 38 different free-licence images of Jimmy Wales obtained from Category:Jimmy Wales on Wikimedia Commons, using Stable Diffusion V1-5 as the base model checkpoint to be trained. Specifically, the following images were used as training data:
Using d8ahazard's DreamBooth_V2 fork of Stable Diffusion web UI created by AUTOMATIC1111, a new model based on Stable Diffusion V1-5 (sd-v1-5-pruned-emaonly.ckpt) was created with "pndm" selected as the scheduler, and the following options were chosen:
The model was then subsequently trained using the 38 images listed earlier. The DreamBooth training process, along with the image generation process outlined later below, was performed using an NVIDIA RTX 4090; since Ada Lovelace chipsets (using compute capability 8.9, which requires CUDA 11.8) are not fully supported by the pyTorch dependency libraries currently used by Stable Diffusion, I've used a custom build of xformers, along with pyTorch cu116 and cuDNN v8.6, as a temporary workaround. After completion of the training of the new model, a batch of 768x1024 images were generated with txt2img in Stable Diffusion, using the model checkpoint taken at 1000 training steps, and with the following prompts:
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日期 | |
来源 | 自己的作品 |
作者 | Benlisquare |
授权 (二次使用本文件) |
As the creator of the output images, I release this image under the licence displayed within the template below.
The Stable Diffusion AI model is released under the CreativeML OpenRAIL-M License, which "does not impose any restrictions on reuse, distribution, commercialization, adaptation" as long as the model is not being intentionally used to cause harm to individuals, for instance, to deliberately mislead or deceive, and the authors of the AI models claim no rights over any image outputs generated, as stipulated by the license.
The Stable Diffusion implementation of DreamBooth by XavierXiao, of which d8ahazard's DreamBooth_V2 fork of the Stable Diffusion web UI is based on, is licenced under the MIT License.
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当前 | 2023年8月8日 (二) 10:35 | ![]() | 2,304 × 2,048(5.14 MB) | Obscure2020(留言 | 贡献) | Optimized with OxiPNG and ZopfliPNG. |
2022年11月4日 (五) 18:47 | ![]() | 2,304 × 2,048(6.04 MB) | Benlisquare(留言 | 贡献) | {{Information |Description=Demonstration of the use of DreamBooth to fine-tune a text-to-image diffusion model (in this particular case, Stable Diffusion) so that it can algorithmically generate highly specialised and customised image outputs. This demonstration features six output images of Jimmy Wales, founder of Wikipedia, performing bench press exercises... |
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