Laughing 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 yourself or your friends laugh!

Features

• 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

A man with dark hair wearing an orange jacket is shown in front of a brown background. He starts by looking into the camera and smiling and then he starts l4a6ing laughing. He's still l4a6ing laughing at the end.

Prompt

A man with dark hair is looking into the camera smiling and then he starts l4a6ing laughing. He's still l4a6ing laughing at the end.

Prompt

A man with gray hair and a gray t-shirt is smiling at the camera. He then begins l4a6ing laughing.

Model File and Inference Workflow

📥 Download Links:

• laughing_15_epochs.safetensors - LoRA Model File
• wan_img2vid_lora_workflow.json - Wan I2V with LoRA Workflow for ComfyUI

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Recommended Settings

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

Trigger Words

The key trigger phrase is: l4a6ing laughing

Prompt Template

For prompting, check out the example prompts; this way of prompting seems to work very well.

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 55 seconds of video comprised of 12 short clips (each clip captioned separately) of people laughing.
• Epochs: 5

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!