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    NIN_Captioer (Krea2 auto caption/LoRA Training/LoRA Test AIO tool) - v0.2.0
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    NIN_Captioer — Local AI Captioning, Krea 2 LoRA Train & Test

    NIN_Captioer is a Windows desktop tool for the full Caption → Train → Test loop. Start by preparing LoRA datasets with local Auto Caption and bilingual review, then train a native Krea 2 LoRA and verify results image.

    Scope: Training is Krea 2 only (train on Krea-2-Raw).
    Other bases (SD / SDXL / Flux, etc.) are not supported for training.
    Tested on: Windows x64 + NVIDIA RTX 4090 only. Other GPUs / OS setups are untested.


    Core Features

    Auto Natural Language Captioning

    • Seamlessly connects to LM Studio or Ollama via local APIs

    • Uses local Vision-LLM models to generate detailed natural language captions suited for Flux / Krea2-style datasets

    • Optional WD14 Danbooru tags (ONNX) for tag-style captioning

    • Batch Auto Caption for images missing .txt, plus reCaption for the current image

    • Caption Analysis: coverage, LoRA Health Score, category distributions

    Real-Time Translation & Side-by-Side Comparison

    • Instant side-by-side bilingual translation next to English captions

    • Review, verify, and fine-tune AI captions without language barriers

    • Edits on either side stay in sync (default target: Traditional Chinese)

    Lora Train (Krea 2 only)

    • Native Krea 2 LoRA trainer in-app (Raw train → Turbo apply / sample)

    • Multi-job Start / Stop, progress log, loss chart, sample previews

    • Loss spike markers and OOM detection surfaced in the UI and log

    • Resource monitor (CPU / RAM / GPU)

    • Low VRAM helpers: layer offload, quantization, gradient checkpointing

    • Hugging Face model Download / Update, Python path probe and install helper

    • LoRA export compatible with ComfyUI key format

    Lora Test (ComfyUI)

    • Install / start / stop ComfyUI from the app

    • Generate with trained Krea 2 checkpoints, multi-prompt runs, and a result gallery

    • Smoke-test LoRAs right after training without switching tools


    Suggested workflow

    1. Add your image folder → connect LM Studio / Ollama

    2. Auto Caption → review with translation → Analyze Health Score

    3. Lora Train (Krea 2 Raw / Turbo) → Start Train

    4. Lora Test → start ComfyUI → pick checkpoint → generate & review gallery


    Description

    Lora Train

    Native Krea 2 trainer on Krea-2-Raw.

    Lora Test

    Install / start / stop ComfyUI from the app. Apply trained LoRAs on Krea-2-Turbo, multi-prompt generate, live ComfyUI log, and a result gallery with filters.

    Comments (2)

    one903045Aug 23, 2026
    CivitAI

    caption function only select 1024 * 1024? Can't I choose other sizes

    NekoInNight
    Author
    Aug 25, 2026

    The image size bucket preview in the caption function is strictly for LoRA training. The caption function uses the full-sized image for caption analysis. Also you can add supported resolutions under LoRA Trainer > Dataset.

    Other
    Other

    Details

    Downloads
    20
    Platform
    CivitAI
    Platform Status
    Available
    Created
    7/31/2026
    Updated
    9/25/2026
    Deleted
    -

    Files

    ninCaptioerKrea2AutoCaption_v020.zip

    Mirrors