Dream Dildo — Experimental LTX2.3 LoRA

This LoRA is provided as-is, strictly for experimental purposes.
It is a motion LoRA for image-to-video generation. It guides the base model toward a specific type of motion/action, shaping how the subject moves rather than altering identity or appearance. The output is always driven by your input image, your prompt, and the capabilities already present in the underlying base model.

No identity-targeted datasets were used in training, and the LoRA does not reconstruct, swap, or expose any specific person's likeness. It only influences motion and action dynamics.

I take no responsibility for your generations. Anything you create with this LoRA is entirely your own responsibility. By downloading or using it, you agree to comply with all applicable laws and platform rules.

Hey everyone! 👋 This is my second attempt at training my own LoRA, and today I'm sharing my experimental release of Dildo LoRA.

This LoRA is rank 32, trained on 40 videos over 2000 steps. It works exclusively in I2V mode and may produce weird results in T2V, so keep that in mind. For input, I feed in characters generated with Gemini or Qwen Image Edit.

It's trained on a side pose, so it can give unpredictable results when you add extra stuff to the prompt. I'm planning to train future versions on different angles and situations — so stay tuned for updates and new versions!

For inference I run the LoRA at weight 1.0. I also stack it with Synth Pussy at weight 0.85 for more realistic anatomy.

I also built my own training program, Just LTX Trainer, so you can train a LoRA without touching a terminal — you can read about it here.

Thanks for checking it out, and any support or feedback means a lot! Either way, I'll keep experimenting and sharing my results for free. ❤️

Basic prompt:

```

DR3AM_DILD0 The girl teleports into a standing erotic pose, holding a dildo in her hands. The girl makes cyclical movements with the dildo deep into her vagina.

```

This prompt was user in all my inference generations and as caption in training