--- language: - en tags: - stable-diffusion - text-to-image license: bigscience-bloom-rail-1.0 inference: false --- # waifu-diffusion - Diffusion for Weebs waifu-diffusion is a latent text-to-image diffusion model that has been conditioned on high-quality anime images through [Textual Inversion](https://github.com/rinongal/textual_inversion). Prompt: touhou 1girl komeiji_koishi portrait ## Model Description The model originally used for fine-tuning is [Stable Diffusion V1-4](https://huggingface.co./CompVis/stable-diffusion-v1-4), which is a latent image diffusion model trained on [LAION2B-en](https://huggingface.co./datasets/laion/laion2B-en). The current model has been fine-tuned with a learning rate of 5.0e-5 for 1 epoch on 56k Danbooru text-image pairs which all have an aesthetic rating greater than `6.0`. ## Training Data & Annotative Prompting The data used for Textual Inversion has come from a random sample of 56k Danbooru images, which were filtered based on [CLIP Aesthetic Scoring](https://github.com/christophschuhmann/improved-aesthetic-predictor) where only images with an aesthetic score greater than `6.0` were used. Captions are Danbooru-style captions. ## Downstream Uses This model can be used for entertainment purposes and as a generative art assistant. ## Example Code ```python import torch from torch import autocast from diffusers import StableDiffusionPipeline model_id = "hakurei/waifu-diffusion" device = "cuda" pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16, revision='fp16') pipe = pipe.to(device) prompt = "touhou hakurei_reimu 1girl solo portrait" with autocast("cuda"): image = pipe(prompt, guidance_scale=7.5)["sample"][0] image.save("reimu_hakurei.png") ``` ## Team Members and Acknowledgements This project would not have been possible without the incredible work by the [CompVis Researchers](https://ommer-lab.com/). - [Anthony Mercurio](https://github.com/harubaru) - [Salt](https://github.com/sALTaccount/)