Making you wish you had three hands!Works for WAN2.2 a14b t2v and i2v.All example videos generated using both high &amp; low lora at strength 1.0When using V2, prompt for specific breast sizes using <code>she has three {small|medium|large|huge} breasts</code> and prompt for bare breasts with <code>she has three exposed {small|medium|large|huge} breasts</code><span style="background-color:rgb(26, 27, 30);color:rgb(193, 194, 197);font-family:-apple-system, BlinkMacSystemFont, &quot;Segoe UI&quot;, Roboto, Helvetica, Arial, sans-serif, &quot;Apple Color Emoji&quot;, &quot;Segoe UI Emoji&quot;;font-size:16px">All showcase videos have workflow embedded. (Use the download button to preserve it, if you Right-click/save-as the workflow data gets stripped by the browser)<h2 id="about-v2.1"><span style="background-color:rgb(26, 27, 30);color:rgb(193, 194, 197);font-family:-apple-system, BlinkMacSystemFont, &quot;Segoe UI&quot;, Roboto, Helvetica, Arial, sans-serif, &quot;Apple Color Emoji&quot;, &quot;Segoe UI Emoji&quot;;font-size:16px">About V2.1</h2>V2.1 should have less of a bias towards cropping out faces and work better when using WAN2.2 without lightx2v.Mostly identical training images and videos, but redid the captions and tweaked some of the training settings.Changes:<ul><li>Captions now specifically include cropped out faces (which appears to have reduced its bias towards defaulting to cropped faces)</li><li>epochs: 100 → 50</li><li>Low-noise<ul><li>lr: 5e-5 → 1e-4</li><li>max_t: 0.875 → 0.6</li></ul></li><li>High-noise<ul><li>min_t: 0.875 → 0.5</li><li>timestep_sample_method: logit_normal → uniform</li></ul></li></ul>

Triboob - three breasts - Wan2.2

This version should have less of a bias towards cropping out faces and work better when using WAN2.2 without lightx2v.Mostly identical training images and videos, but redid the captions and tweaked some of the training settings.Changes:<ul><li>Captions now specifically include cropped out faces (which appears to have reduced its bias towards defaulting to cropped faces)</li><li>epochs: 100 → 50</li><li>Low-noise<ul><li>lr: 5e-5 → 1e-4</li><li>max_t: 0.875 → 0.6</li></ul></li><li>High-noise<ul><li>min_t: 0.875 → 0.5</li><li>timestep_sample_method: logit_normal → uniform</li></ul></li></ul>

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