Wanted to use customized pipelines and other components (schedulers, unets, text encoders, etc.) in Diffusers?
Found it inflexible?
Since the first dawn on earth, we have supported loading custom pipelines via a custom_pipeline argument 🌄
These pipelines are inference-only, i.e., the assumption is that we're leveraging an existing checkpoint (e.g., runwayml/stable-diffusion-v1-5) and ONLY modifying the pipeline implementation.
We have many cool pipelines, implemented that way. They all share the same benefits available to a DiffusionPipeline, no compromise there 🤗
We're introducing experimental support for device_map in Diffusers 🤗
If you have multiple GPUs you want to use to distribute the pipeline models, you can do so. Additionally, this becomes more useful when you have multiple low-VRAM GPUs.