Trained on the iconic gray screen. If applied at a negative weight (for example -0.25), it reliably prevents it from triggering no matter what is in the prompt.

In the attached workflows, the LoRA is only applied at the first step and then disabled. This way there's no quality or aesthetic loss. LoRA being active through the whole generation could lead to degradation. The second workflow (image_ideogram4_t2i_no_gray_screen_lora_example) shows the way any other LoRA would be applied.

The prompt for the first preview picture (the cat) is written in natural language. The second one had a JSON prompt without any bboxes.

That being said, Ideogram is clearly not intended for natural language. Prompt adherence is quite subpar and if the prompt is too short, it could result in a complete mess. So I recommend using this LoRA AND correct JSON prompts as an extra measure to make sure the gray screen never appears, not as a way to use natural language prompts with it.