docs: def predict(dataset, fitmodel_url, save_results=True, show=False):
      """
      Function starts a job that makes predictions to input data with a given model.
  
      Parameters
      ----------
      input - dataset object with input urls and other parameters
      fitmodel_url - model created in fit phase
      save_results - save results to ddfs
      show - show info about job execution
  
      Returns
      -------
      Urls with predictions on ddfs
      """
      from disco.worker.pipeline.worker import Worker, Stage
      from disco.core import Job, result_iterator
  
      if "linsvm_fitmodel" not in fitmodel_url:
          raise Exception("Incorrect fit model.")
  
      job = Job(worker=Worker(save_results=save_results))
      # job parallelizes execution of mappers
      job.pipeline = [
          ("split", Stage("map", input_chain=dataset.params["input_chain"], init=simple_init, process=map_predict))]
  
      job.params = dataset.params
      job.params["fit_params"] = [v for _, v in result_iterator(fitmodel_url["linsvm_fitmodel"])][0]
      job.run(name="linsvm_predict", input=dataset.params["data_tag"])
  
      return job.wait(show=show)