NetaYume Lumina Image v2.0

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I. Introduction

NetaYume Lumina is a text-to-image model fine-tuned from Neta Lumina, a high-quality anime-style image generation model developed by Neta.art Lab. It builds upon Lumina-Image-2.0, an open-source base model released by the Alpha-VLLM team at Shanghai AI Laboratory.

This model was trained with the goal of not only generating realistic human images but also producing high-quality anime-style images. Despite being fine-tuned on a specific dataset, it retains a significant amount of knowledge from the base model.

Key Features:

• High-Quality Anime Generation: Generates detailed anime-style images with sharp outlines, vibrant colors, and smooth shading.
• Improved Character Understanding: Better captures characters, especially those from the Danbooru dataset, resulting in more coherent and accurate character representations.
• Enhanced Fine Details: Accurately generates accessories, clothing textures, hairstyles, and background elements with greater clarity.

The file NetaYume_Lumina_v2_all_in_one.safetensors is an all-in-one file that contains the necessary weights for the VAE, text encoder, and image backbone to be used with ComfyUI.

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II. Model Components & Training Details

• Text Encoder: Pre-trained Gemma-2-2b
• Variational Autoencoder: Pre-trained Flux.1 dev's VAE
• Image Backbone: Fine-tune NetaLumina's Image Backbone

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III. Suggestion

System Prompt: This help you generate your desired images more easily by understanding and aligning with your prompts.

For anime-style images using Danbooru tags:

 You are an assistant designed to generate anime images based on textual prompts. 

 You are an assistant designed to generate high-quality images based on user prompts and  danbooru tags.

Recommended Settings

• CFG: 4–7
• Sampling Steps: 40-50
• Sampler:
  • Euler a (with scheduler: normal)
  • res_multistep (with scheduler: linear_quadratic)

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IV. Acknowledgments

• narugo1992 – for the invaluable Danbooru dataset
• Alpha-VLLM - for creating the a wonderful model!
• Neta.art and his team – for openly sharing awesome model.