I have extracted the Lora from Ernie Image Turbo.

An independent developer has successfully reverse-engineered and released a LoRA (Low-Rank Adaptation) file for Baidu's Ernie Image Turbo, a powerful but commercially restricted AI image generation model. The extracted adapter, shared on the model-sharing platform Civitai.red, provides a rare public window into the technical parameters required to run the model effectively. However, the release comes with a major caveat: the LoRA appears to be highly unstable unless used with a very specific, inflexible set of generation settings.

The developer's tests reveal that the Ernie Image Turbo LoRA demands a generation strength of 1, a minimum of 9 sampling steps, and a CFG (Classifier-Free Guidance) scale of 3 to produce coherent images. Attempting to lower any of these values—a common practice for speeding up generation or achieving different artistic effects—causes the model to 'break,' resulting in severe image deformities and making a persistent grid-like artifact more prominent. This rigidity is unusual compared to more flexible open-source models like Stable Diffusion, suggesting Ernie Image Turbo may use a specialized or heavily optimized architecture that is difficult to fine-tune.

While the leak allows hobbyists and researchers to experiment with a slice of Baidu's proprietary technology, its practical utility is limited by these strict operational constraints. The developer has released the LoRA publicly in hopes that the community can discover more stable settings, turning a technical curiosity into a more usable tool.