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v2.0_qwen/README.md

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+---
+language:
+- en
+tags:
+- art
+---
+
+# Flat Color - Style
+
+**Creator**: [motimalu](https://civitai.com/user/motimalu)
+**Type**: LORA
+**Base Model**: Qwen
+**Version**: v2.0 [qwen]
+**Trigger Words**: `N/A`
+
+**Civitai Model ID**: 1132089
+**Civitai Version ID**: 2143914
+
+**Stats (at time of fetch for this version)**:
+*   Downloads: 917
+*   Rating: 0 (0 ratings)
+*   Favorites: N/A
+
+---
+
+## 📄 Description (Parent Model)
+
+Flat Color
+-
+Style
+Trained on images without visible lineart, flat colors, and
+little to no indication of depth.
+ℹ️ LoRA work best when applied to the base models on which they are trained.
+Please read the
+About This Version
+on the appropriate base models
+and workflow/training information.
+This is a small style LoRA I thought would be interesting to try with a v-pred model (noobai v-pred), for the reduced color bleeding and strong blacks in particular.
+The effect is quite nice and easy to evaluate in training, so I've extended the dataset with videos in following versions for text-to-video models like Wan and Hunyuan, and it is what I am generally using to test LoRA training on new models now.
+Recommended prompt structure:
+Positive prompt:
+flat color, no lineart, blending, negative space,
+{{tags}}
+masterpiece, best quality, very aesthetic, newest
+
+## Version Notes (v2.0 [qwen])
+
+Trained on
+Qwen Image
+Using the default
+diffusion-pipe qwen config
+Dataset resolution of 640
+Previews generated with the lightx2v Lighting 4step LoRA:
+https://huggingface.co/lightx2v/Qwen-Image-Lightning/blob/main/Qwen-Image-Lightning-4steps-V1.0.safetensors
+
+---
+
+## Civitai Links
+
+*   **[🔗 View This Version on Civitai →](https://civitai.com/models/1132089?modelVersionId=2143914)**
+*   [View Full Model Page →](https://civitai.com/models/1132089)
+*   [View Creator Profile →](https://civitai.com/user/motimalu)
+
+---
+
+## File Information
+
+*   **Filename**: `qwen_flat_color_v2.safetensors`
+*   **Size**: 562.72 MB
+*   **Hash (AutoV2)**: `7CF4436A45`
+*   **Hash (SHA256)**: `7CF4436A4597ECC046598654288CF76015039388955C008EFE86FB082622821A`