Extensions/ComfyUI-Flux2Klein9Mod
ComfyUI Extension

ComfyUI-Flux2Klein9Mod

Refmod for Flux2 Klein9

By malcolmamal·Created a day ago·Updated about 20 hours ago· 1
malcolmamal/ComfyUI-Flux2Klein9Mod
Nodes4
On cloudLocal install
Categorymodel/conditioning/klein9
Stars1
Updatedabout 20 hours ago

Nodes (4)

Apply Klein9 RefMods (FLUX.2)

Stop Re-Encoding Your References on Every Single Run

model/conditioning/klein9
Extract Klein9 RefMod (FLUX.2)

Turn a Pile of Reference Photos Into One Reusable Latent File

model/conditioning/klein9
Load RefMod Folder (Images)

It Reads Your Disk, and the Default Path Is the Author's

model/conditioning/klein9
Load Klein9 RefMods (FLUX.2)

Eight Slots, Three Dials, and a Dropdown That's Empty Until It Isn't

model/conditioning/klein9
Readme

ComfyUI-Flux2Klein9Mod

No-training "RefMod" reference adapters for FLUX.2 and Klein9.

RefMods pre-encode reference images and datasets into compact, reusable .safetensors adapters stored in models/refmods-klein9/. Rather than loading and VAE-encoding raw 4K/1024px image files on every generation run (which adds 4096+ tokens and heavy attention latency), RefMods inject pre-computed reference latents directly into the FLUX.2 / Klein9 2D RoPE sequence with instant loading, zero VAE overhead, and full multi-character scaling.

🔗 Links & Resources

📦 Features

  • Pre-encoded Latent Storage: Stored in ComfyUI/models/refmods-klein9/.
  • Zero VAE Generation Latency: Latents are loaded directly from disk without runtime VAE encoding.
  • Configurable Token Budgets: Native resolution or spatial pooling to target budgets (e.g. 512, 1024, 2048 tokens).
  • Multi-Subject Scaling: Load up to 8 distinct RefMods simultaneously (mod_1 through mod_8) with independent strengths.
  • Manifold Blending: Smooth weakening and strength attenuation using spatial low-pass filtering along the latent manifold instead of noise degradation.
  • Universal Compatibility: Works with any standard ComfyUI CONDITIONING graph for FLUX.2, Klein 4B, Klein 8B, and Klein 9B models.

🚀 Installation

  1. Navigate to your ComfyUI custom_nodes folder: 
    cd ComfyUI/custom_nodes
  2. Clone or place this repository: 
    git clone https://github.com/malcolmrey/ComfyUI-Flux2Klein9Mod.git
  3. Ensure the model folder exists: 
    ComfyUI/models/refmods-klein9/
  4. Restart ComfyUI.

🧩 Nodes

| Node Name | Category | Description | | :--- | :--- | :--- | | Load Klein9 RefMods (FLUX.2) (Klein9RefModsLoader) | model/conditioning/klein9 | Loads 1–8 RefMod .safetensors files from models/refmods-klein9/ with individual strengths (0.0–3.0) and repeat counts. | | Apply Klein9 RefMods (FLUX.2) (Klein9RefModApply) | model/conditioning/klein9 | Injects the loaded RefMod bundle into standard ComfyUI CONDITIONING (reference_latents). | | Extract Klein9 RefMod (FLUX.2) (Klein9RefModExtract) | model/conditioning/klein9 | In-graph VAE encode & token compression of input images directly into a saved .safetensors file in models/refmods-klein9/. | | Load RefMod Folder (Images) (Klein9RefModFolderLoader) | model/conditioning/klein9 | Batch loads an entire folder of reference images for extraction. |

🛠️ Graph Wiring

[ CLIPTextEncode ] (Prompt) 
         │
         ▼
[ Apply Klein9 RefMods (FLUX.2) ] ◄── [ Load Klein9 RefMods (FLUX.2) ]
         │ (conditioning out)          (Selects models from models/refmods-klein9/)
         ▼
[ CFGGuider / SamplerCustomAdvanced ]

💻 CLI Extraction Tool

You can also pre-encode image datasets using the CLI:

python custom_nodes/ComfyUI-Flux2Klein9Mod/extract_klein9_mod.py \
  --name fk9_billieeilish_v1_refmod \
  --dataset-dir C:/Development/ai-toolkit/datasets/billieeilish \
  --concept-type identity \
  --token-budget 1024 \
  --output-dir C:/Development/ComfyUI/models/refmods-klein9/