Introduction of Spontaneous-Combustion-Redmond-WAN2-I2V-14B
Model Details of Spontaneous-Combustion-Redmond-WAN2-I2V-14B
Spontaneous Combustion LoRA for Wan I2V
Prompt
Spontaneous Combustion
Prompt
Spontaneous Combustion
Prompt
Spontaneous Combustion
Prompt
Spontaneous Combustion
Prompt
Spontaneous Combustion
Special Thanks:
This project was made possible thanks to generous sponsorship and GPU time provided by
reDMOND Ai
.
We are grateful for their support in training this LoRA.
Model Description
This LoRA specializes in creating dramatic spontaneous combustion effects from static images. Transform ordinary objects into scenes of sudden, mysterious ignition with realistic fire propagation, smoke, and ember effects. Perfect for creating suspenseful, supernatural, or dramatic moments in your videos where objects burst into flames without any external trigger.
This version is specifically adapted for use with
Wan-AI Image-to-Video
models, like
Wan2.2-I2V-A14B
.
Trigger Words
The trigger phrase is
Spontaneous Combustion
.
For best results, use "Spontaneous Combustion" in your prompt when describing the scene you want to animate. The model will transform your static image into a dynamic combustion sequence.
Setup for ComfyUI
To use this LoRA in ComfyUI, simply place the file in your
loras
directory:
Download
[WAN2.2]Spontaneous_Combustion_Redmond_low_noise.safetensors
and
[WAN2.2]Spontaneous_Combustion_Redmond_high_noise.safetensors
and place them in
ComfyUI/models/loras/
Ensure your ComfyUI environment is already configured to run Wan I2V models.
Example Workflow (ComfyUI)
In your ComfyUI workflow, add a
Load LoRA
node after your base model loader.
Load your base
Wan I2V
model.
Connect the output of the model loader to the
model
input of the
Load LoRA
node.
Select either
[WAN2.2]Spontaneous_Combustion_Redmond_low_noise.safetensors
and
[WAN2.2]Spontaneous_Combustion_Redmond_high_noise.safetensors
in the Load LoRA node.
Connect the
MODEL
output of the LoRA node to your KSampler.
Adjust the
strength_model
as needed (0.8-1.0 is a good starting point).
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