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v1.0__hunyuan/README.md

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+---
+language:
+- en
+tags:
+- art
+---
+
+# Flat Color - Style
+
+**Creator**: [motimalu](https://civitai.com/user/motimalu)
+**Type**: LORA
+**Base Model**: Hunyuan Video
+**Version**: v1.0 [hunyuan]
+**Trigger Words**: `flat color, no lineart`
+
+**Civitai Model ID**: 1132089
+**Civitai Version ID**: 1282350
+
+**Stats (at time of fetch)**:
+*   Downloads: 345
+*   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 (v1.0 [hunyuan])
+
+Trained as a small experiment with
+https://github.com/tdrussell/diffusion-pipe
+Gives a charming flat color style to Hunyuan t2v generations
+
+---
+
+## Civitai Links
+
+*   **[🔗 View This Version on Civitai →](https://civitai.com/models/1132089?modelVersionId=1282350)**
+*   [View Full Model Page →](https://civitai.com/models/1132089)
+*   [View Creator Profile →](https://civitai.com/user/motimalu)
+
+---
+
+## Preview Images
+
+![Preview Image](./previews/1282350_51578097.mp4)
+
+---
+
+## File Information
+
+*   **Filename**: `hunyuan_flat_color.safetensors`
+*   **Size**: 615.08 MB
+*   **Hash (AutoV2)**: `2FDC063D98`
+*   **Hash (SHA256)**: `2FDC063D9816F51BE533509E8BBE6CB6C6CFE5156B569DB5B5ED06EE0E91AC01`
+