Update README.md

README.md

@@ -1,9 +1,8 @@
-# 🚀 ComfyUI Workflows by wizdroid
+---
+license: mit
+---
 
-[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)
-[![ComfyUI](https://img.shields.io/badge/ComfyUI-Workflows-blue)](https://github.com/comfyanonymous/ComfyUI)
-[![Flux](https://img.shields.io/badge/Flux-Accelerated-orange)](https://blackforestlabs.ai/)
-[![Nunchaku](https://img.shields.io/badge/Nunchaku-Fast%20Inference-purple)](https://github.com/nunchaku-tech)
+# 🚀 ComfyUI Workflows by wizdroid
 
 **High-quality, production-ready ComfyUI workflows** focused on **character consistency**, fast generation, and automated dataset creation for LoRA training.
 
@@ -19,123 +18,98 @@ These workflows power consistent character generation, multi-reference image-to-
 - **SeedVR2 Upscaler** — One of the best image upscalers available (DiT + VAE with advanced tiling & color correction)
 - **WizdroidLoRADataset** — Custom node for automated vision-LLM captioning, dataset structuring, and validation — perfect companion for training consistent characters
 - **LoRA-ready** — Built-in toggleable LoRA loading across most pipelines
-- **Square 1:1 + Flexible Resolutions** — Optimized for character reference work and social media / print use cases
+- **Square 1:1 + Flexible Resolutions** — Optimized for character reference work
 
-> **Pro Tip:** Pair these workflows with the [Consistent Character Reference Prompts](https://github.com/wizdroid/comfyui-workflows) (40+ square 1:1 variations covering angles, expressions, beauty, upper/full body, and profiles) for unbeatable training data.
+> **Pro Tip:** Pair these workflows with the **[Consistent Character Reference Prompts (PROMPTS.md)](https://huggingface.co/wizdroid/comfyui-workflows/blob/main/PROMPTS.md)** (40+ square 1:1 variations covering angles, expressions, beauty, upper/full body, and profiles) for unbeatable training data.
 
 ---
 
 ## 📁 Workflows
 
-| Workflow                  | Type          | Size    | Key Features                                      | Best For |
-|---------------------------|---------------|---------|---------------------------------------------------|----------|
-| `flux2-klein-t2i.json`    | Text-to-Image | ~23 MB  | Nunchaku Flux2-Klein 9B, advanced Flux sampler, LoRA support | High-quality prompt-driven generation |
-| `flux2-klein-1i2i.json`   | 1-Image Ref   | ~29 MB  | Single reference image + Reference Latent         | Strong character consistency from one photo |
-| `flux2-klein-2i2i.json`   | 2-Image Ref   | ~35 MB  | Dual reference images                             | Even stronger identity with two angles/expressions |
-| `flux2-klein-3i2i.json`   | 3-Image Ref   | ~41 MB  | Triple reference images + advanced conditioning   | Maximum character fidelity (recommended for LoRA training) |
-| `qwen-t2i.json`           | Text-to-Image | ~14 MB  | Qwen-based, flexible resolution, LoRA             | Alternative aesthetic / artistic control |
-| `qwen-aio-t2i.json`       | Text-to-Image | ~12 MB  | Qwen All-in-One variant                           | Quick Qwen generations |
-| `qwen-aio-1i2i.json`      | 1-Image Ref   | ~14 MB  | Qwen image reference                              | Qwen-powered character consistency |
-| `qwen-aio-2i2i.json`      | 2-Image Ref   | ~15 MB  | Dual reference                                    | Multi-ref Qwen |
-| `qwen-aio-3i2i.json`      | 3-Image Ref   | ~16 MB  | Triple reference                                  | Maximum Qwen consistency |
-| `z-image-turbo-t2i.json`  | Fast T2I      | ~18 MB  | Z-Image-Turbo (very few steps), Nunchaku          | Lightning-fast prototyping & iteration |
-| `seedvr2-i2i.json`        | Upscaler      | ~13 MB  | SeedVR2 DiT + VAE upscaler, tiling, color correction | Best-in-class 2×–4× upscaling & detail recovery |
-| `dataset-generator.json`  | Dataset Tool  | ~3 MB   | WizdroidLoRADataset + Ollama vision (Moondream)   | Automated LoRA training dataset creation with captions |
+| Workflow                  | Type          | Key Features                                      | Best For |
+|---------------------------|---------------|---------------------------------------------------|----------|
+| `flux2-klein-t2i.json`    | Text-to-Image | Nunchaku Flux2-Klein 9B, advanced Flux sampler, LoRA support | High-quality prompt-driven generation |
+| `flux2-klein-1i2i.json`   | 1-Image Ref   | Single reference image + Reference Latent         | Strong character consistency from one photo |
+| `flux2-klein-2i2i.json`   | 2-Image Ref   | Dual reference images                             | Even stronger identity with two angles/expressions |
+| `flux2-klein-3i2i.json`   | 3-Image Ref   | Triple reference images + advanced conditioning   | **Maximum character fidelity** (recommended for LoRA training) |
+| `qwen-t2i.json`           | Text-to-Image | Qwen-based, flexible resolution, LoRA             | Alternative aesthetic / artistic control |
+| `qwen-aio-t2i.json`       | Text-to-Image | Qwen All-in-One variant                           | Quick Qwen generations |
+| `qwen-aio-1i2i.json`      | 1-Image Ref   | Qwen image reference                              | Qwen-powered character consistency |
+| `qwen-aio-2i2i.json`      | 2-Image Ref   | Dual reference                                    | Multi-ref Qwen |
+| `qwen-aio-3i2i.json`      | 3-Image Ref   | Triple reference                                  | Maximum Qwen consistency |
+| `z-image-turbo-t2i.json`  | Fast T2I      | Z-Image-Turbo (very few steps), Nunchaku          | Lightning-fast prototyping & iteration |
+| `seedvr2-i2i.json`        | Upscaler      | SeedVR2 DiT + VAE upscaler, tiling, color correction | Best-in-class 2×–4× upscaling & detail recovery |
+| `dataset-generator.json`  | Dataset Tool  | WizdroidLoRADataset + Ollama vision (Moondream)   | Automated LoRA training dataset creation with captions |
 
 ---
 
 ## 🛠️ Installation & Setup
 
 ### 1. ComfyUI
-Make sure you have a recent [ComfyUI](https://github.com/comfyanonymous/ComfyUI) installation.
+Recent [ComfyUI](https://github.com/comfyanonymous/ComfyUI) installation.
 
 ### 2. Required Custom Nodes
-Install these via **ComfyUI Manager** (recommended) or git clone into `custom_nodes/`:
+Install via **ComfyUI Manager** (recommended):
 
-- **ComfyUI-nunchaku** — For accelerated Flux inference
-- **ComfyUI-SeedVR2_VideoUpscaler** (ainvfx) — For the SeedVR2 upscaler workflow
-- **Wizdroid Character Dataset Node** — The custom `WizdroidLoRADataset` node (included in this repo's ecosystem)
+- **ComfyUI-nunchaku** — Accelerated Flux inference
+- **ComfyUI-SeedVR2_VideoUpscaler** (ainvfx)
+- **Wizdroid Character Dataset Node** (WizdroidLoRADataset and related nodes)
 
-Restart ComfyUI after installing custom nodes.
+Restart ComfyUI after installing.
 
 ### 3. Models
-Place models in the standard ComfyUI folders (or update paths inside workflows):
-
-**Flux2-Klein (main quality engine):**
-- `flux/2/flux2-klein-9B.safetensors`
-- `flux/2/vae.safetensors`
-
-**Qwen:**
-- `qwen/qwen-image-edit-sfw.safetensors`
-- `qwen/qwen3-8B.safetensors` (or 4B variant)
-- `qwen/qwen3-4B.safetensors`
-
-**Z-Image Turbo:**
-- `z-image/z-image-turbo.safetensors`
-- `z-image/vae.safetensors`
-- `z-image/turbo/4nup4m4.safetensors` (example turbo LoRA)
-
-**SeedVR2:**
-- `seedvr2_ema_7b_sharp_fp16.safetensors` (DiT)
-- `ema_vae_fp16.safetensors` (VAE)
+Place in standard ComfyUI folders:
 
-**CLIP / Other:**
-- Various Qwen CLIP models as referenced in the workflows
-
-### 4. Ollama (for Dataset Generator)
-The `dataset-generator.json` workflow uses a local vision model via Ollama:
+- **Flux2-Klein**: `flux/2/flux2-klein-9B.safetensors` + VAE
+- **Qwen** models (as referenced in workflows)
+- **Z-Image-Turbo** + turbo LoRAs
+- **SeedVR2**: `seedvr2_ema_7b_sharp_fp16.safetensors` + VAE
 
+### 4. Ollama (Dataset Generator)
 ```bash
-# Install Ollama and pull a good vision model (Moondream recommended in the workflow)
 ollama pull moondream:latest
+ollama serve
 ```
 
-Start Ollama (`ollama serve`) before running the dataset workflow. You can change the model/URL inside the node.
-
 ---
 
 ## 🚀 How to Use
 
-1. **Load a workflow**: Drag & drop any `.json` file directly onto your ComfyUI canvas, or use **Load** → select the file.
-2. **Queue Prompt** as usual.
-3. Most workflows expose clean proxy widgets on the right for:
-   - Prompt / negative prompt
-   - Seed, steps, CFG, sampler
-   - Width / Height
-   - LoRA toggle + strength
-   - Reference images (for i2i workflows)
+1. Drag & drop any `.json` workflow onto ComfyUI.
+2. Use the clean proxy widgets for prompt, seed, steps, LoRA toggle, and reference images.
+3. For **character consistency**, load prompts from **[PROMPTS.md](https://huggingface.co/wizdroid/comfyui-workflows/blob/main/PROMPTS.md)** into the 1i2i/2i2i/3i2i workflows.
 
-### Character Consistency Workflow Recommendations
+**Recommended for LoRA training data:** `flux2-klein-3i2i.json` + 2–3 clean source references + the 40 reference prompts.
 
-- Use **flux2-klein-3i2i.json** (or 2i2i) with 2–3 high-quality, varied reference photos of your character.
-- Generate using the same character across many angles/expressions using the reference prompts collection.
-- Feed the resulting images into `dataset-generator.json` to auto-caption and structure a ready-to-train dataset (with your character trigger tag).
+Then run `dataset-generator.json` to auto-caption and structure everything with your trigger word.
 
 ---
 
-## 💡 Tips for Best Results
+## 💡 Full Guide: Mastering Consistent Characters
 
-- **Reference Images**: Clean, well-lit, minimal makeup/jewelry/background. Square 1:1 references work great.
-- **Prompting**: Start simple ("Photo of a woman", "beautiful detailed face") and let the reference images do the heavy lifting for identity.
-- **LoRAs**: The LoRA switch is disabled by default in many workflows. Enable it and point to character or style LoRAs.
-- **Speed vs Quality**: Use `z-image-turbo-t2i.json` for rapid iteration, then switch to Flux2-Klein for final outputs.
-- **Upscaling**: Always run important generations through `seedvr2-i2i.json` for that extra polish.
-- **Dataset Quality**: Use the dataset generator + good reference images + Ollama captions, then manually review the `validation_report`.
+For the complete step-by-step tutorial (problem → solution → pipeline with these workflows + PROMPTS.md + WizdroidLoRADataset → pro tips), see the dedicated CivitAI article:
 
----
+**→ [Mastering Consistent Characters for LoRA Training](https://civitai.com/articles/...)**  
+*(Replace with the real link after publishing the article on CivitAI)*
 
-## 📜 License
+It covers why single-ref fails, how Reference Latent + the 40 square prompts solve identity drift, generating 40–100+ training images, auto-captioning with the custom node, and training best practices.
 
-MIT License — feel free to use, modify, and share these workflows.
+This short README is the HF model card version. The full rich version is in the local `README.md`.
 
 ---
 
-## 🤝 Contributing
+## 📜 License
 
-Pull requests and workflow improvements are welcome! If you create amazing results with these, tag **@wizdroid** — I'd love to see what you build.
+MIT — use, modify, and share freely.
 
 ---
 
 **Made with ❤️ for the ComfyUI community by wizdroid**
 
 *Consistent characters start with great references and great tools.*
+
+---
+
+**Additional Resources**
+- [PROMPTS.md — 40 Consistent Character Reference Prompts](https://huggingface.co/wizdroid/comfyui-workflows/blob/main/PROMPTS.md)
+- Full workflows and updates in this repository