 explicitly convert the model parameters to bfloat16 precision to do full
half-precision training or to save weights in bfloat16 for inference in order to save memory and improve speed.

Examples:


	Copied
>>> from diffusers import FlaxUNet2DConditionModel

>>> # load model
>>> model, params = FlaxUNet2DConditionModel.from_pretrained("runwayml/stable-diffusion-v1-5")
>>> # By default, the model parameters will be in fp32 precision, to cast the