> You can use SDXL refiner with a different base model. For example, you can use the [Hunyuan-DiT](../../api/pipelines/hunyuandit) or [PixArt-Sigma](../../api/pipelines/pixart_sigma) pipelines to generate images with better prompt adherence. Once you have generated an image, you can pass it to the SDXL refiner model to enhance final generation quality.
> You can use SDXL refiner with a different base model. For example, you can use the [Hunyuan-DiT](../api/pipelines/hunyuandit) or [PixArt-Sigma](../api/pipelines/pixart_sigma) pipelines to generate images with better prompt adherence. Once you have generated an image, you can pass it to the SDXL refiner model to enhance final generation quality.
Generate an image from the base model, and set the model output to **latent** space:
@@ -280,5 +280,5 @@ This is really what 🧨 Diffusers is designed for: to make it intuitive and eas
For your next steps, feel free to:
* Learn how to [build and contribute a pipeline](../using-diffusers/contribute_pipeline) to 🧨 Diffusers. We can't wait and see what you'll come up with!
* Learn how to [build and contribute a pipeline](../conceptual/contribution) to 🧨 Diffusers. We can't wait and see what you'll come up with!
* Explore [existing pipelines](../api/pipelines/overview) in the library, and see if you can deconstruct and build a pipeline from scratch using the models and schedulers separately.