docs: remove fabricated BibTeX citation and clean credits

README.md

@@ -7,71 +7,51 @@ tags:
 - inpainting
 - qwen-image
 - qwen-image-2512
-- videox-fun
 - quantized
 - int8
 - convrot
 - comfyui
 pipeline_tag: image-to-image
-library_name: videox_fun
 ---
 
 # ControlNet Models (ConvRot INT8)
 
-High-fidelity **ConvRot INT8** quantized weights for diffusion ControlNet models. This repository provides memory-efficient INT8 quantized checkpoints maintaining high structural fidelity and multi-condition guidance.
+High-fidelity **ConvRot INT8** quantized weights for ControlNet models.
 
 ---
 
 ## 🌟 Model Overview
 
-This repository hosts the **ConvRot INT8** quantized edition of **`Qwen-Image-2512-Fun-Controlnet-Union-2602`**, originally developed and trained by **Alibaba PAI / VideoX-Fun**.
-
-The **ConvRot INT8** format applies rotational transformation matrix optimizations to suppress outlier activations and minimize quantization error, reducing the model footprint to **~1.64 GB** (from ~3.3+ GB FP16) while preserving multi-condition structural precision.
+This repository hosts the **ConvRot INT8** quantized weights of **`Qwen-Image-2512-Fun-Controlnet-Union-2602`**, based on [alibaba-pai/Qwen-Image-2512-Fun-Controlnet-Union](https://huggingface.co/alibaba-pai/Qwen-Image-2512-Fun-Controlnet-Union).
 
 - **Base Model:** [alibaba-pai/Qwen-Image-2512-Fun-Controlnet-Union](https://huggingface.co/alibaba-pai/Qwen-Image-2512-Fun-Controlnet-Union)
-- **Architecture:** Multi-condition Union ControlNet added across 5 layer blocks of Qwen-Image-2512.
-- **Quantization:** Full ConvRot INT8 (weights stored with rotational transformations).
+- **Supported Conditions:** Canny, HED, Depth, Pose, MLSD, Scribble, Gray, Inpainting
+- **Quantization:** ConvRot INT8
 - **License:** Apache-2.0
 
 ---
 
 ## 📦 Available Models
 
-| Filename | Base Architecture | Supported Conditions | Precision | File Size | License |
+| Filename | Base Model | Supported Conditions | Precision | File Size | License |
 | :--- | :--- | :--- | :--- | :--- | :--- |
-| `Qwen-Image-2512-Fun-Controlnet-Union-2602_convrot_int8.safetensors` | Qwen-Image-2512 (5 Layer Blocks) | Canny, HED, Depth, Pose, MLSD, Scribble, Gray, Inpaint | ConvRot INT8 | ~1.64 GB | Apache-2.0 |
-
----
-
-## 🛠️ Supported Control Modalities & Features
-
-1. **Union Condition Architecture**:
-   Supports unified multi-condition control within a single checkpoint:
-   - **Pose** (OpenPose / DWPose keypoints)
-   - **Canny** (Edge detection)
-   - **HED** (Soft edge detection)
-   - **Depth** (Z-depth estimation)
-   - **MLSD** (Straight-line wireframe extraction)
-   - **Scribble** (Interactive doodle / sketch guidance)
-   - **Gray** (Grayscale / luminance guidance)
-2. **Inpainting Mode Support**:
-   Fully compatible with masked inpainting pipelines (`Pose + Inpaint`, `Depth + Inpaint`, etc.).
-3. **Multi-Resolution Conditioning**:
-   Extracting control maps in multi-resolution formats improves generalization across arbitrary target aspect ratios.
+| `Qwen-Image-2512-Fun-Controlnet-Union-2602_convrot_int8.safetensors` | Qwen-Image-2512-Fun-Controlnet-Union-2602 | Canny, HED, Depth, Pose, MLSD, Scribble, Gray, Inpaint | ConvRot INT8 | ~1.64 GB | Apache-2.0 |
 
 ---
 
-## ⚙️ Recommended Inference Settings
+## 🛠️ Model Features
 
-- **`control_context_scale`**: Optimal range is **`0.70` – `0.95`**. Higher values yield stronger adherence to the control input, while lower values offer increased prompt stylization freedom.
-- **Prompt Formulation**: Detailed natural language descriptions significantly enhance semantic stability and detail preservation.
-- **Resolution**: Multi-scale aspect ratios matching the base Qwen-Image model resolution specifications.
+- ControlNet added on 5 layer blocks of Qwen-Image-2512.
+- Supports multiple control conditions: Canny, HED, Depth, Pose, MLSD, Scribble, Gray.
+- Inpainting mode is supported.
+- Acquiring control images in a multi-resolution manner results in better generalization.
+- Optimal range for `control_context_scale` is from 0.70 to 0.95.
 
 ---
 
 ## 🚀 Usage in ComfyUI
 
-Standard / vanilla ComfyUI does not natively support the **ConvRot INT8** format for ControlNet models. To load and execute these weights, the dedicated loader extension is required:
+ComfyUI does not natively support the **ConvRot INT8** format for ControlNet models. To load and execute these weights in ComfyUI, the dedicated loader extension is required:
 
 - **Dedicated Loader Extension:** [ComfyUI-HSWQ-Loader-and-Tools](https://github.com/ussoewwin/ComfyUI-HSWQ-Loader-and-Tools)
 
@@ -84,28 +64,12 @@ cd ComfyUI/custom_nodes
 git clone https://github.com/ussoewwin/ComfyUI-HSWQ-Loader-and-Tools.git
 ```
 
-Place `Qwen-Image-2512-Fun-Controlnet-Union-2602_convrot_int8.safetensors` into your ComfyUI `models/controlnet/` folder and load it using the dedicated loader nodes from the extension.
+Place `Qwen-Image-2512-Fun-Controlnet-Union-2602_convrot_int8.safetensors` into your ComfyUI `models/controlnet/` directory and load it using the dedicated loader node.
 
 ---
 
-## 📜 Credits & Citation
-
-### Upstream Creators
-Deep gratitude and acknowledgement to the **Alibaba PAI VideoX-Fun Team** for developing, training, and open-sourcing the Qwen-Image ControlNet series.
-- **Original Model:** [alibaba-pai/Qwen-Image-2512-Fun-Controlnet-Union](https://huggingface.co/alibaba-pai/Qwen-Image-2512-Fun-Controlnet-Union)
-- **Official Repository:** [aigc-apps/VideoX-Fun](https://github.com/aigc-apps/VideoX-Fun)
-
-```bibtex
-@misc{videox_fun,
-  author = {VideoX-Fun Team},
-  title = {VideoX-Fun: A Flexible Video and Image Generation Toolset},
-  year = {2025},
-  publisher = {GitHub},
-  journal = {GitHub repository},
-  howpublished = {\url{https://github.com/aigc-apps/VideoX-Fun}}
-}
-```
-
----
+## 📜 Credits & License
 
-**Disclaimer:** These model weights are released strictly for research, non-commercial, and optimization workflows under the Apache-2.0 License.
+- **Original Base Model:** [alibaba-pai/Qwen-Image-2512-Fun-Controlnet-Union](https://huggingface.co/alibaba-pai/Qwen-Image-2512-Fun-Controlnet-Union)
+- **Upstream Repository:** [aigc-apps/VideoX-Fun](https://github.com/aigc-apps/VideoX-Fun)
+- **License:** Apache-2.0