Raehoshi Illust XL

an enhanced iteration built upon the Illustrious XL model. It aims to elevate the visual style by addressing some of the limitations in the original, such as oversaturation and artifact noise. While these issues are not entirely eliminated, noticeable improvements have been made. The goal is to deliver a more polished, balanced output while staying true to the strengths of the base model.

Why Early Access?

Early access helps keep the project going. I don’t have my own GPU, so all training is done through rented cloud GPUs and that gets pretty expensive. By getting early access, you’re directly supporting the development of my models and helping me keep improving them. If you'd like to support me further, you can also buy me a coffee on Ko-fi! Every bit of help means a lot and keeps the future updates coming.

Recommended setting

Positive prompt :

masterpiece, best quality, very aesthetic, absurdres

Negative prompt :

bad quality, worst quality, jpeg artifacts, sketch, bad anatomy, signature, watermark

Steps : 25+

CFG : 5-7

Sampler : euler a or dpm++2m karras (euler for vpred)

Standard resolution :

832 x 1216, 1216 x 832,  1152 x 896, 896 x 1152, 1344 x 768, 768 x 1344, 1024 x 1024

High resolution :

1024 x 1536, 896 x 1536, 1536 x 1024, 1536 x 896

Hires.fix Setting:

• Upscaler : 4x Foolhardy Remacri

• Hires step : 10-15

• Denoise : 0.1-0.3

Special Tags

Quality Tags:

• masterpiece

• best quality

• good quality

• average quality

• bad quality

• worst quality

Rating Tags:

• safe

• sensitive

• nsfw

• nsfw, explicit

Aesthetic Tags:

• very aesthetic

• aesthetic

• displeasing

• very displeasing

Training Details

The model was developed using a two-stage fine-tuning process. In Stage 1, new series and characters were introduced into the model. Stage 2 focused on fixing issues and enhancing the overall style for improved output.

Stage 1

• Dataset : v1-31k, v2-37k, v3-34k, v4-60k, v5_v5.1-18k, v6-15k, v7-39k, v8-41k, v9-30k, v10-30k with multi resolution

• Hardware : 2x A100 80gb, v3, v4, v5, v5.1-2x H100 80gb, v7,v8, v9, v10-RTX PRO 6000

• Batch size : 32

• Gradient accumulation steps : 2

• Learning rate : 6e-6

• Text encoder : 3e-6

• Epoch : 15

Stage 2

• Dataset : v1-2.5k, v2 and v3-2.3k, v4-2.5k, v5-2k, v5.1-1.8k, v6-1.5k, v7-1.7k, v7.1,v8-4.1k, v9-1.9k, v10-2.4k

• Hardware : 1x A100 80gb, v7_v7.1,v8, v9, v10-RTX PRO 6000

• Batch size : 48

• Gradient accumulation steps : 1

• Learning rate : 3e-6, v5.1-2.5e-6

• Text encoder : disable

• Epoch : 15

List of New Series/Characters Trained:

• Zenless Zone Zero

• Wuthering Waves

• Honkai: Star Rail

• Genshin Impact

• Arknights: Endfield

• Umamusume

• Azur Lane

• Arknights

• Fate/GO

• Dandadan

• Make heroine ga oo sugiru

• Kusuriya no Hotorigoto

• Hololive from justice and dev is

• Indie Vtuber Dooby, Yuuki Sakuna, Nimi Nightmare, and S***

• 100 girlfriends who really love you

• Haite kudasai takamine-san

• Alina clover

• Nikke: bready and little mermaid

• Kpop Demon Hunters

Full character list are available article here

For character trait details prompts, please refer to the Danbooru site for accurate tags and references.

License

Fair AI Public License 1.0-SD

Special thanks to Joe for supporting my works

Special thanks to Juno for supporting my works and help me with early tester