precision to do full
half-precision training or to save weights in float16 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 params will be in fp32, to cast these to float16
>>> params = model.to_fp16(params)
>>> # If you want d