My first T2V test, still experimenting on that. For generations I’m using 15–30 steps, a CFG of 7, and an 6 step shift for videos ranging from 32 to 64+ frames.The sweet spot for weight seems to be working 0.6-1.0, got some decent results with 0.8 but I haven't tested T2V directly that much, it should be working but my experience is low quality compared to I2V.As usual I just picked some generated images randomly from civit pushed concept loras, kudos to creators.No trigger word used in the training. I recommend focusing on the action and little bit of general details. Milking and table are pretty common words in the training data.Here’s an example prompt I used in one of these generations—feel free to alter it heavily:<pre><code>A woman with [color] hair, [clothing and general look], is positioned under a milking table, [performing oral sex on /// grips] a large, erect, circumcised penis hanging down from above dripping cum. She is actively milking the penis as semen dripping down onto her chest. The background is white and simple.</code></pre>I’m still experimenting the training process, so feel free to share your generations. This will help me gather more feedback to improve further. I didn’t have a large dataset to begin with and trained on relatively low settings if anyone’s curious.Since this is an NSFW-capable model, please use it responsibly. No real person faces were used in the training and the rest is heavily anonymized.

Files with SHA256: ccefda0400320e050a6635eb23444dec6774f6c3810634f44b2188c35a43cdb8