# Image variation The Stable Diffusion model can also generate variations from an input image. It uses a fine-tuned version of a Stable Diffusion model by [Justin Pinkney](https://www.justinpinkney.com/) from [Lambda](https://lambdalabs.com/). The original codebase can be found at [LambdaLabsML/lambda-diffusers](https://github.com/LambdaLabsML/lambda-diffusers#stable-diffusion-image-variations) and additional official checkpoints for image variation can be found at [lambdalabs/sd-image-variations-diffusers](https://huggingface.co/lambdalabs/sd-image-variations-diffusers). Make sure to check out the Stable Diffusion [Tips](./overview#tips) section to learn how to explore the tradeoff between scheduler speed and quality, and how to reuse pipeline components efficiently! ## StableDiffusionImageVariationPipeline [[autodoc]] StableDiffusionImageVariationPipeline - all - __call__ - enable_attention_slicing - disable_attention_slicing - enable_xformers_memory_efficient_attention - disable_xformers_memory_efficient_attention ## StableDiffusionPipelineOutput [[autodoc]] pipelines.stable_diffusion.StableDiffusionPipelineOutput