/ Модель

Характеристики

Лицензия
CreativeML OpenRAIL-M
Опубликована
18 янв 2023

Anything-Preservation

Генерация изображенийТекст → изображение3 профессии

Сохранённая версия Anything V3 с улучшенным VAE для генерации детализированных изображений в аниме-стиле по текстовым запросам и тегам Danbooru.

712скачиваний за 30 дней106лайковвеса обновлены27 янв 2023

Бенчмарки

Как модель справилась с задачами пользователей ailist и что о ней публикуют открытые лидерборды

Тесты пользователейпока нет

Никто ещё не опубликовал тест этой модели. Соберите бенчмарк из своих задач — результат появится здесь.

  1. Добавьте модель в бенчмарк

    Вместе с другими моделями категории «Изображения» — сравнение идёт внутри одной категории.

  2. Опишите свои задачи

    Напишите запросы, при необходимости приложите файлы и эталонные ответы.

  3. Запустите и опубликуйте

    Модели сгенерируют результат по каждой задаче. Опубликованный тест появится на этой странице.

Публичные оценки

Из открытых лидербордов. Сравнивайте результаты одного теста при одинаковых условиях — отсутствие оценки не значит, что модель хуже.

В подключённых источниках результатов для этой модели пока нет.

Что умеет модель

Описание составлено по карточке модели и метаданным Hugging Face

AdamOswald1/Anything-Preservation — репозиторий сохранения модели Anything V3 с улучшенным VAE, представленной в форматах Diffusers, ckpt и safetensors. Это латентная диффузионная модель на базе Stable Diffusion, разработанная для генерации детализированных изображений в аниме-стиле по текстовым запросам. Она понимает короткие описания и теги Danbooru, поэтому подходит для создания персонажей и сцен в характерной стилистике аниме.

Модель рассчитана на генерацию изображений через Stable Diffusion и совместима с Diffusers; в карточке также упоминаются варианты экспорта ONNX, MPS и Flax/JAX. README описывает репозиторий как архивную копию и указывает на неофициальное продолжение Anything V4.0. Лицензия — CreativeML OpenRAIL-M.

Сценарии применения

  • создание аниме-персонажей по текстовому описанию
  • генерация иллюстраций по тегам Danbooru
  • создание фантастических пейзажей в аниме-стиле

Ограничения

Репозиторий обозначен как архив сохранения; README указывает на неофициальное продолжение модели Anything V4.0. Качество и результаты зависят от формулировки запроса и настроек генерации.

Для каких профессий подходит3

Разделы каталога профессий, в задачах которых используется эта модель

Все профессии

Карточка модели

README от автора на Hugging Face, как он его опубликовал

Открыть на Hugging Face

DISCLAIMER! This Is A Preservation Repository!

Anything V3 - Better VAE

Welcome to Anything V3 - Better VAE. It currently has three model formats: diffusers, ckpt, and safetensors. You'll never see a grey image result again. This model is designed to produce high-quality, highly detailed anime-style images with just a few prompts. Like other anime-style Stable Diffusion models, it also supports danbooru tags for image generation. e.g. 1girl, white hair, golden eyes, beautiful eyes, detail, flower meadow, cumulonimbus clouds, lighting, detailed sky, garden

Gradio

We support a Gradio Web UI to run Anything V3 with Better VAE:

Open In Spaces

🧨 Diffusers

This model can be used just like any other Stable Diffusion model. For more information, please have a look at the Stable Diffusion. You can also export the model to ONNX, MPS and/or FLAX/JAX.

You should install dependencies below in order to running the pipeline

pip install diffusers transformers accelerate scipy safetensors

Running the pipeline (if you don't swap the scheduler it will run with the default DDIM, in this example we are swapping it to DPMSolverMultistepScheduler):

from diffusers import StableDiffusionPipeline, DPMSolverMultistepScheduler

model_id = "Linaqruf/anything-v3-0-better-vae"

# Use the DPMSolverMultistepScheduler (DPM-Solver++) scheduler here instead
pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16)
pipe.scheduler = DPMSolverMultistepScheduler.from_config(pipe.scheduler.config)
pipe = pipe.to("cuda")

prompt = "masterpiece, best quality, illustration, beautiful detailed, finely detailed, dramatic light, intricate details, 1girl, brown hair, green eyes, colorful, autumn, cumulonimbus clouds, lighting, blue sky, falling leaves, garden"
negative_prompt = "lowres, bad anatomy, bad hands, text, error, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality, normal quality, jpeg artifacts, signature, watermark, username, blurry, artist name"

with autocast("cuda"):
    image = pipe(prompt, 
                 negative_prompt=negative_prompt, 
                 width=512,
                 height=640,
                 guidance_scale=12,
                 num_inference_steps=50).images[0]
    
image.save("anime_girl.png")

Examples

Below are some examples of images generated using this model:

Anime Girl: Anime Girl

Anime Boy: Anime Boy

Scenery: Scenery

License

This model is open access and available to all, with a CreativeML OpenRAIL-M license further specifying rights and usage. The CreativeML OpenRAIL License specifies:

  1. You can't use the model to deliberately produce nor share illegal or harmful outputs or content
  2. The authors claims no rights on the outputs you generate, you are free to use them and are accountable for their use which must not go against the provisions set in the license
  3. You may re-distribute the weights and use the model commercially and/or as a service. If you do, please be aware you have to include the same use restrictions as the ones in the license and share a copy of the CreativeML OpenRAIL-M to all your users (please read the license entirely and carefully) Please read the full license here

Announcement

For (unofficial) continuation of this model, please visit andite/anything-v4.0. I am aware that the repo exists because I am literally the one who (accidentally) gave the idea to publish his fine-tuned model (andite/yohan-diffusion) as a base and merged it with many mysterious model, "hey, let's call it 'Anything V4.0'", because the quality is quite similar to Anything V3 but upgraded.

I also wanted to tell you something. I had a plan to remove/make private one of each repo named "Anything V3":

Because there are two versions now and I'm late to realize this mysterious non-sense model is already polluted Huggingface Trending for so long, and now when the new repo comes out it is also there. I feel guilty everytime this model is in trending leaderboard.

I prefer to delete/make private this one and let us slowly move to Linaqruf/anything-v3-better-vae with better repo management and a better VAE included in the model.

Please share your thoughts in this #133 discussion about whether I should delete this repo or another one, or maybe both of them.

Thanks, Linaqruf.


Anything V3

Welcome to Anything V3 - a latent diffusion model for weebs. This model is intended to produce high-quality, highly detailed anime style with just a few prompts. Like other anime-style Stable Diffusion models, it also supports danbooru tags to generate images.

e.g. 1girl, white hair, golden eyes, beautiful eyes, detail, flower meadow, cumulonimbus clouds, lighting, detailed sky, garden

Gradio

We support a Gradio Web UI to run Anything-V3.0:

Open in Spaces

🧨 Diffusers

This model can be used just like any other Stable Diffusion model. For more information, please have a look at the Stable Diffusion.

You can also export the model to ONNX, MPS and/or FLAX/JAX.

from diffusers import StableDiffusionPipeline
import torch

model_id = "Linaqruf/anything-v3.0"
branch_name= "diffusers"

pipe = StableDiffusionPipeline.from_pretrained(model_id, revision=branch_name, torch_dtype=torch.float16)
pipe = pipe.to("cuda")

prompt = "pikachu"
image = pipe(prompt).images[0]

image.save("./pikachu.png")

Examples

Below are some examples of images generated using this model:

Anime Girl: Anime Girl

1girl, brown hair, green eyes, colorful, autumn, cumulonimbus clouds, lighting, blue sky, falling leaves, garden
Steps: 50, Sampler: DDIM, CFG scale: 12

Anime Boy: Anime Boy

1boy, medium hair, blonde hair, blue eyes, bishounen, colorful, autumn, cumulonimbus clouds, lighting, blue sky, falling leaves, garden
Steps: 50, Sampler: DDIM, CFG scale: 12

Scenery: Scenery

scenery, shibuya tokyo, post-apocalypse, ruins, rust, sky, skyscraper, abandoned, blue sky, broken window, building, cloud, crane machine, outdoors, overgrown, pillar, sunset
Steps: 50, Sampler: DDIM, CFG scale: 12

License

This model is open access and available to all, with a CreativeML OpenRAIL-M license further specifying rights and usage. The CreativeML OpenRAIL License specifies:

  1. You can't use the model to deliberately produce nor share illegal or harmful outputs or content
  2. The authors claims no rights on the outputs you generate, you are free to use them and are accountable for their use which must not go against the provisions set in the license
  3. You may re-distribute the weights and use the model commercially and/or as a service. If you do, please be aware you have to include the same use restrictions as the ones in the license and share a copy of the CreativeML OpenRAIL-M to all your users (please read the license entirely and carefully) Please read the full license here

Как запустить

На своей GPU в ailist. Цена — по текущим предложениям провайдеров

GPU в ailist

Универсальный рантайм

Можно запустить

Подбираем GPU…

Ревизия весов
cfdfefe

0 моделей