class_docstr: Unembedding parameter. This will likely be mapped to the same original weight in the model as the
  embedding, but we have a different preferred sharding approach.
class_docstr_tok: ["Unembedding","parameter",".","This","will","likely","be","mapped","to","the","same","original","weight","in","the","model","as","the","embedding",",","but","we","have","a","different","preferred","sharding","approach","."]
code: def finalize(self) -> torch.Tensor:
      return self.inference_model.transform_unembed_param(self.params)
  
imports: import torch
  from ...model_implementations.parameter_base import ParameterBase
label_desc: Use image node_id 1 for calling the UnembedParameter obj's underlying member method code with example usage: obj.finalize() and returns: self