Mona Lisa Effect LoRA for Wan2.1 14B I2V 480p

Overview

This LoRA is trained on the Wan2.1 14B I2V 480p model and allows you to make any person/object in an image become a Mona Lisa version of themselves!

Features

  • Transform any image into a video of the subject as a Mona Lisa version of themselves!
  • Trained on the Wan2.1 14B 480p I2V base model
  • Consistent results across different object types
  • Simple prompt structure that's easy to adapt

Community

  • Discord: Join our community to generate videos with this LoRA for free
  • Request LoRAs: We're training and open-sourcing Wan2.1 LoRAs for free - join our Discord to make requests!
Prompt
The video starts with an image of a woman. The m0n4 Mona Lisa transformation begins as a dark sheet seems to wrap around the woman, and when the image resolves, the woman is depicted as a Mona Lisa version of itself. The Mona Lisa version of the woman sits in a chair with a backdrop featuring a landscape painting.
Prompt
The video starts with an image of a man wearing a suit. The m0n4 Mona Lisa transformation begins as a dark sheet seems to wrap around him, and when the image resolves, he is depicted as a Mona Lisa version of himself. The Mona Lisa version sits in a chair with a backdrop featuring a landscape painting.

Model File and Inference Workflow

πŸ“₯ Download Links:


Recommended Settings

  • LoRA Strength: 1.0
  • Embedded Guidance Scale: 6.0
  • Flow Shift: 5.0

Trigger Words

The key trigger phrase is: m0n4 Mona Lisa transformation

Prompt Template

For best results, try following the structure of the prompt examples above. These worked well for me.

ComfyUI Workflow

This LoRA works with a modified version of Kijai's Wan Video Wrapper workflow. The main modification is adding a Wan LoRA node connected to the base model.

See the Downloads section above for the modified workflow.

Model Information

The model weights are available in Safetensors format. See the Downloads section above.

Training Details

  • Base Model: Wan2.1 14B I2V 480p
  • Training Data: Trained on 35 seconds of video comprised of 7 short clips (each clip captioned separately) of people transforming into Mona Lisa!
  • Epochs: 45

Additional Information

Training was done using Diffusion Pipe for Training

Acknowledgments

Special thanks to Kijai for the ComfyUI Wan Video Wrapper and tdrussell for the training scripts!

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