SeeSee21 / AniSee

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🖼️ Preview Gallery

Browse the full curated set of sample images on the dedicated gallery page:

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✨ What is AniSee?

AniSee is a personal full fine-tune of CircleStone Labs' Anima Preview3 Base , retrained on my own curated dataset to push the model further into a cleaner, more focused anime aesthetic.

It is not a LoRA merge — AniSee is a full fine-tune (~20K steps) with the LLM adapter only very lightly co-trained , following the official Anima fine-tuning guidelines. The goal is to keep everything that makes Anima a strong illustration base — Danbooru tags, natural language prompts, mixed prompts, full Qwen text encoder, Qwen-Image VAE — while shifting the default style toward a stronger anime look in line with my other checkpoints.

AniSee is mainly intended for:

• Anime-style illustrations
• Character-focused images
• Cleaner anime aesthetics
• Style experiments
• Testing Anima-based fine-tunes inside ComfyUI

This is the first release — only the Diffusion Model variant for now. If testing goes well, an AIO version and a 4-Step Turbo version (based on the new CDM — Continuous-Time Distribution Matching distillation method) will follow.

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🎯 Key Features

• ✅ Full fine-tune on Anima Preview3 Base — not a LoRA merge
• ✅ ~20K training steps on a curated anime dataset
• ✅ Clean, focused anime aesthetics
• ✅ Supports Danbooru-style tags , natural language , and mixed prompts
• ✅ Compatible with the standard Anima ComfyUI workflow
• ✅ Drop-in replacement for anima-preview3-base.safetensors
• ✅ Uses the existing Qwen text encoder + Qwen-Image VAE — included in the repo
• ✅ LoRA training friendly — same base architecture as Anima

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🗺️ AniSee Roadmap

✅ Released

🎨 AniSee Base

Full fine-tune of Anima Preview3 Base — Diffusion Model variant. This is the foundation of the AniSee family.

🔜 Planned

📦 AniSee AIO

All-in-one checkpoint with Diffusion Model + Qwen Text Encoder + Qwen-Image VAE integrated into a single file. Single-file convenience, no extra loaders needed.

🚀 AniSee Turbo (4-Step, CDM)

If testing of the Base goes well, a 4-Step Turbo variant distilled with the brand-new Continuous-Time Distribution Matching (CDM) method (Liu et al., 2026). CDM migrates the DMD framework from discrete anchoring to continuous optimization, achieving state-of-the-art few-step generation without GAN or reward-model auxiliary objectives . Should give clean 4-step anime generations with strong fine details.

📄 Paper: https://byliutao.github.io/cdm_page/

🔧 Official AniSee ComfyUI Workflow

A dedicated workflow with the auto-prefix, optional Qwen3-VL prompt enhancer, LoRA support, and Ultimate SD Upscale is already included in this repo under workflows/AniSee.json .

More updates coming as testing progresses! 🎨

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⚙️ AniSee Base — Recommended Settings

The settings I personally use and recommend as a starting point:

Steps:       40
CFG:         4.5
Sampler:     er_sde
Scheduler:   simple
Resolution:  ~1 MP   # e.g. 1024×1024, 896×1152, 1152×896

CFG Guide: 4.0–5.0 is the sweet spot for balanced quality and creativity. Going above 5.0 starts to risk burning the image, especially with heavy quality tags. If results feel too harsh, drop CFG slightly or reduce quality tag count.

Sampler alternatives (all work well, just different character):

Feel free to experiment — these are just starting points, not hard rules.

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📐 Resolution Guide

Stay around 1 MP for the cleanest results. The Anima base starts breaking down somewhere around 2 MP, so if you want bigger images, generate at 1 MP first and upscale afterwards.

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💡 Prompting Guide

AniSee inherits Anima's prompting system. It accepts:

• Danbooru / anime-style tags
• Natural language prompts
• Mixed prompts (tags + sentences)

A good prompt structure:

[quality tags] [meta tags] [safety tag] [subject (1girl/1boy/etc)]
[character] [appearance] [pose] [clothing] [background] [lighting] [style]

Important tag rules (inherited from Anima):

• Use lowercase for tags, spaces instead of underscores
• Score tags are the only tags that use underscores ( score_7 , etc.)
• Artist tags must be prefixed with @ — e.g. @artistname

✅ Good (mixed prompt)

masterpiece, best quality, score_7, highres, illustration, safe, 1girl,
long silver hair, blue eyes, black hoodie, standing in a rainy city street
at night, neon lights reflecting on wet asphalt, cinematic lighting,
detailed anime illustration

✅ Good (natural language)

masterpiece, best quality, score_7, highres, illustration.
A young anime girl with long silver hair and golden eyes, wearing a
traditional shrine maiden outfit with white haori and red hakama.
She stands in a sunlit bamboo forest, cherry blossoms falling softly
around her. Warm afternoon light filtering through the trees,
detailed fabric shading, calm serene expression.

❌ Avoid

Very short tag dumps like anime girl, silver hair, hoodie — the model can produce unexpected results when the prompt is too sparse. Aim for at least a few descriptive tags or 2+ sentences.

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⭐ Recommended Positive Prefix

Start every prompt with:

masterpiece, best quality, score_7, highres, illustration,

Then add your subject, character, scene, and style tags after that.

You can also experiment with other quality tag combinations:

• masterpiece, best quality, score_7, safe (Anima default)
• masterpiece, best quality, score_8, highres, official art
• score_9, masterpiece, absurdres, anime screenshot

But the prefix above is what I personally use and recommend as a starting point.

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⭐ Recommended Negative Prompt

This is the negative I run with — it cleans up most common issues without being so aggressive that it kills the style:

worst quality, low quality, score_1, score_2, score_3, artist name,
(lowres:1.2), (worst quality:1.4), (low quality:1.4), (bad anatomy:1.4),
bad hands, multiple views, comic, jpeg artifacts, patreon logo,
patreon username, web address, signature, watermark, artist name,
censored, mosaic censoring

If your images come out too flat or lose style, reduce the weights on the heavier terms (e.g. drop (low quality:1.4) back to low quality ).

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🛡️ Safety Tags

Inherited from Anima. Use one of these in the positive prompt:

• safe — for normal generations (recommended default)
• sensitive
• nsfw
• explicit

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🔧 Installation

Step 1 — Download the files

You need three files (all included in this repo):

• anisee.safetensors — the model
• text_encoders/qwen_3_06b_base.safetensors — text encoder
• vae/qwen_image_vae.safetensors — VAE

Step 2 — Place the files

ComfyUI/models/diffusion_models/
└── anisee.safetensors

ComfyUI/models/text_encoders/
└── qwen_3_06b_base.safetensors

ComfyUI/models/vae/
└── qwen_image_vae.safetensors

If you already run Anima Preview3 Base , you already have the text encoder and VAE — AniSee is a direct drop-in.

Step 3 — Load in ComfyUI

Use the standard Anima workflow, or the official AniSee workflow from workflows/anisee-workflow-SDUltimate.json :

• Load Diffusion Model → anisee.safetensors
• Load Text Encoder → qwen_3_06b_base.safetensors
• Load VAE → qwen_image_vae.safetensors

Then your usual sampler, encode, decode, save chain.

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🧩 Official Workflow

A ready-to-use ComfyUI workflow is included at workflows/anisee-workflow-SDUltimate.json .

It features:

• 📦 Model + Text Encoder + VAE loaders pre-configured
• 🔗 Auto Quality Prefix — no need to type masterpiece, best quality, score_7, ... yourself
• 🎲 Optional Qwen3-VL Prompt Enhancer — converts short one-liners into full Danbooru tag lists
• 📖 Optional LoRA stack via Lora Manager (one-click toggle)
• 🔼 Optional UltimateSDUpscale 2× with side-by-side compare
• 🎨 Pre-configured with er_sde / simple / 40 steps / CFG 4.5
• ➖ Pre-loaded recommended negative prompt
• 📝 Built-in MarkdownNote with all settings + quick reference

Required custom nodes (all installable via ComfyUI Manager):

• ComfyUI-Easy-Use
• ComfyUI_UltimateSDUpscale
• ComfyUI-Lora-Manager
• ComfyUI-QwenVL
• rgthree-comfy

For the optional 2× upscaler, also place 4x-UltraSharp.pth in ComfyUI/models/upscale_models/ :

• OpenModelDB — 4x-UltraSharp
• HuggingFace — Kim2091/UltraSharp

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📁 Repository Structure

AniSee/
├── README.md
├── config.json
│
├── anisee.safetensors                    # the model (~4.18 GB)
│
├── text_encoders/
│   └── qwen_3_06b_base.safetensors       # text encoder (same as Anima)
│
├── vae/
│   └── qwen_image_vae.safetensors        # VAE (same as Anima)
│
├── images/
│   ├── cover.png                         # social preview / model cover
│   ├── anisee-workflow-cover.png         # workflow preview image
│   ├── 1.png   2.png   3.png   4.png
│   ├── 5.png   6.webp  7.webp  8.png
│   ├── 9.png   10.png  11.webp 12.webp
│   └── ...
│
└── workflows/
    └── anisee-workflow-SDUltimate.json

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📈 Version History

v1.0 — Initial Release

• AniSee Base — full fine-tune of Anima Preview3 Base
• ~20K training steps on a curated anime dataset
• LLM adapter only very lightly co-trained (following Anima's fine-tuning guidelines)
• Diffusion Model variant (single .safetensors file)
• Compatible with the standard Anima ComfyUI workflow
• Drop-in replacement for anima-preview3-base.safetensors
• Includes the official ComfyUI workflow with auto quality prefix + Qwen3-VL prompt enhancer

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🔗 Links

• CivitAI Page: civitai.red/models/2628747/anisee
• Example Gallery: anisee.anisee.workers.dev
• Base Model: circlestone-labs/Anima
• CDM Paper (planned Turbo variant) : byliutao.github.io/cdm_page
• Author: SeeSee21 on Hugging Face

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🙏 Credits

• Base Model: Anima Preview3 Base by CircleStone Labs and Comfy Org
• Underlying Architecture: Built on NVIDIA Cosmos-Predict2-2B (Anima is a "Derivative Model")
• Fine-Tune: SeeSee21
• CDM Distillation Method (planned Turbo variant) : Continuous-Time Distribution Matching for Few-Step Diffusion Distillation — Liu et al., 2026
• Workflow Custom Nodes: yolain, ssitu, Will Miao, AILab (1038lab), rgthree

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📜 License

AniSee inherits the CircleStone Labs Non-Commercial License from Anima. The model and derivatives are usable only for non-commercial purposes . As a derivative of Cosmos-Predict2-2B-Text2Image, the NVIDIA Open Model License Agreement also applies insofar as it covers Derivative Models.

For commercial licensing of the base model, please contact CircleStone Labs at [email protected] .

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❤️ Notes

AniSee is a personal anime-focused fine-tune of Anima Preview3 Base, built to bring a stronger anime look and visual direction in line with my other checkpoints.

It is still in active testing — the AIO and 4-Step Turbo (CDM) variants will follow once the Base has been validated in the wild.

AniSee — clean anime, built on Anima. 🎨