[Feature Request] SDXL on 16G RAM (model unload)
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- Python
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Description
Currently SDXL base+refiner can`t be used at the same time if you have only 16G of RAM. Separate model works perfectly.
Constantly switching between models is very annoying since you need to change workflow and pictures.
However, loading model from SSD only takes about 10 seconds. This time is comparable to one iteration on my GTX 1650 ti (~8 s).
Possible solution:
Can base model be "unloaded" from RAM after first stage is finished and loaded back at the next generation? (obviously, same is need for refiner model)
Loading model from SSD is safe and much more faster than using swap on HDD.
Something like extra node "unload" with trigger activation or an "unload model after generation" parameter at the sampler node would be fine.
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