---
license: apache-2.0
language:
- en
base_model:
- Wan-AI/Wan2.1-I2V-14B-480P
- Wan-AI/Wan2.1-I2V-14B-480P-Diffusers
pipeloute_tag: image-to-video
tags:
- text-to-image
- lora
- diffusers
- template:diffusion-lora
- image-to-video
widget:
- text: >-
      The video begins with a close-up on a man's face, his hands tied with rope, and an anxious expression. Then, a cr34sh crash zoom out effect reveals a dark and obscure room, the man is still tied up and two men wearing balaklavas and holding guns appear to be standing behind him. 
  output:
    url: example_videos/1.mp4
- text: >-
      The video begins with a close-up on the man's face, with ice covering his beard and eyelashes. He has a concerned or startled expression, his eyes are a vivid blue.  A cr34sh crash zoom out effect rapidly pulls the camera back, revealing the man in a yellow jacket set in a icy landscape. The cr34sh crash zoom out effect shows his position: standing on the edge of the sea with icebergs in the background. 
  output:
    url: example_videos/2.mp4
- text: >-
      The video begins with a close-up shot of a woman's face with intricate black and white tribal markings on her face, neck, and chest. Her eyes are closed and she is wearing dark red eyeshadow and lipstick. The cr34sh crash zoom out effect then begins, quickly pulling back to reveal that the woman is in a dimly lit room, with candles all around her. 
  output:
    url: example_videos/3.mp4
---

<div style="background-color: #f8f9fa; padding: 20px; border-radius: 10px; margin-bottom: 20px;">
  <h1 style="color: #24292e; margin-top: 0;">Crash zoom out LoRA for Wan2.1 14B I2V 480p</h1>
  
  <div style="background-color: white; padding: 15px; border-radius: 8px; margin: 15px 0; box-shadow: 0 2px 4px rgba(0,0,0,0.1);">
    <h2 style="color: #24292e; margin-top: 0;">Overview</h2>
    <p>Abruptly zooms out from the subject to reveal the surrounding scene, creating a sudden sense of scale, surprise, or disorientation. Ideal for dramatic or comedic reveals.This LoRA is trained on the Wan2.1 14B I2V 480p model.
</p>
  </div>

  <div style="background-color: white; padding: 15px; border-radius: 8px; margin: 15px 0; box-shadow: 0 2px 4px rgba(0,0,0,0.1);">
    <h2 style="color: #24292e; margin-top: 0;">Features</h2>
    <ul style="margin-bottom: 0;">
      <li>Trained on the Wan2.1 14B 480p I2V base model</li>
      <li>Consistent results across different object types</li>
      <li>Simple prompt structure that's easy to adapt</li>
    </ul>
  </div>

  <div style="background-color: white; padding: 15px; border-radius: 8px; margin: 15px 0; box-shadow: 0 2px 4px rgba(0,0,0,0.1);">
  <h2 style="color: #24292e; margin-top: 0;">Community</h2>
  <ul style="margin-bottom: 0;">
    <li>
      Generate videos with 100+ Camera Control and VFX LoRAs on the 
      <a href="https://app.remade.ai/canvas/create" style="color: #0366d6; text-decoration: none;">Remade Canvas</a>.
    </li>
    <li>
      <b>Discord:</b> 
      <a href="https://remade.ai/join-discord?utm_source=Huggingface&utm_medium=Social&utm_campaign=model_release&utm_content=crash_zoom_out" style="color: #0366d6; text-decoration: none;">
        Join our community
      </a> to generate videos with this LoRA for free
    </li>
  </ul>
</div>

<Gallery />

# Model File and Inference Workflow

## 📥 Download Links:

- [crash_zoom_out.safetensors](./crash_zoom_out.safetensors) - LoRA Model File
- [wan_img2vid_lora_workflow.json](./workflow_I2V/wan_img2vid_lora_workflow.json) - Wan I2V with LoRA Workflow for ComfyUI

---
<div style="background-color: #f8f9fa; padding: 20px; border-radius: 10px; margin-bottom: 20px;">
  <div style="background-color: white; padding: 15px; border-radius: 8px; margin: 15px 0; box-shadow: 0 2px 4px rgba(0,0,0,0.1);">
    <h2 style="color: #24292e; margin-top: 0;">Recommended Settings</h2>
    <ul style="margin-bottom: 0;">
      <li><b>LoRA Strength:</b> 1.0</li>
      <li><b>Embedded Guidance Scale:</b> 6.0</li>
      <li><b>Flow Shift:</b> 5.0</li>
    </ul>
  </div>

  <div style="background-color: white; padding: 15px; border-radius: 8px; margin: 15px 0; box-shadow: 0 2px 4px rgba(0,0,0,0.1);">
    <h2 style="color: #24292e; margin-top: 0;">Trigger Words</h2>
    <p>The key trigger phrase is: <code style="background-color: #f0f0f0; padding: 3px 6px; border-radius: 4px;">cr34sh crash zoom out effect</code></p>
  </div>

  <div style="background-color: white; padding: 15px; border-radius: 8px; margin: 15px 0; box-shadow: 0 2px 4px rgba(0,0,0,0.1);">
    <h2 style="color: #24292e; margin-top: 0;">Prompt Template</h2>
    <p>For prompting, check out the example prompts; this way of prompting seems to work very well.</p>


  <div style="background-color: white; padding: 15px; border-radius: 8px; margin: 15px 0; box-shadow: 0 2px 4px rgba(0,0,0,0.1);">
    <h2 style="color: #24292e; margin-top: 0;">ComfyUI Workflow</h2>
    <p>This LoRA works with a modified version of <a href="https://github.com/kijai/ComfyUI-WanVideoWrapper/blob/main/example_workflows/wanvideo_480p_I2V_example_02.json" style="color: #0366d6; text-decoration: none;">Kijai's Wan Video Wrapper workflow</a>. The main modification is adding a Wan LoRA node connected to the base model.</p>
    <img src="./workflow_I2V/workflow_screenshot.png" style="width: 100%; border-radius: 8px; margin: 15px 0; box-shadow: 0 4px 8px rgba(0,0,0,0.1);">
    <p>See the Downloads section above for the modified workflow.</p>
  </div>
</div>

<div style="background-color: #f8f9fa; padding: 20px; border-radius: 10px; margin-bottom: 20px;">
  <div style="background-color: white; padding: 15px; border-radius: 8px; margin: 15px 0; box-shadow: 0 2px 4px rgba(0,0,0,0.1);">
    <h2 style="color: #24292e; margin-top: 0;">Model Information</h2>
    <p>The model weights are available in Safetensors format. See the Downloads section above.</p>
  </div>

  <div style="background-color: white; padding: 15px; border-radius: 8px; margin: 15px 0; box-shadow: 0 2px 4px rgba(0,0,0,0.1);">
    <h2 style="color: #24292e; margin-top: 0;">Training Details</h2>
    <ul style="margin-bottom: 0;">
      <li><b>Base Model:</b> Wan2.1 14B I2V 480p</li>
      <li><b>Training Data:</b> Trained on 50 seconds of video comprised of 10 short clips (each clip captioned separately) of scenes that used the crash zoom out camera motion.</li>
      <li><b> Epochs:</b> 25</li>
    </ul>
  </div>

  <div style="background-color: white; padding: 15px; border-radius: 8px; margin: 15px 0; box-shadow: 0 2px 4px rgba(0,0,0,0.1);">
    <h2 style="color: #24292e; margin-top: 0;">Additional Information</h2>
    <p>Training was done using <a href="https://github.com/tdrussell/diffusion-pipe" style="color: #0366d6; text-decoration: none;">Diffusion Pipe for Training</a></p>
  </div>

  <div style="background-color: white; padding: 15px; border-radius: 8px; margin: 15px 0; box-shadow: 0 2px 4px rgba(0,0,0,0.1);">
    <h2 style="color: #24292e; margin-top: 0;">Acknowledgments</h2>
    <p style="margin-bottom: 0;">Special thanks to Kijai for the ComfyUI Wan Video Wrapper and tdrussell for the training scripts!</p>
  </div>
</div>