Prediction Configuration

RIME performs some model profiling in order to measure its overall performance. Depending on the dataset size and model throughput, profiling can be time-consuming. We provide some options to speed this process up.

Template

{
    "prediction_info": {
        "ref_path": null,
        "eval_path": null,
        "n_samples": null
    },
    ...
}

Arguments

• ref_path: string or null, default = null

  Path to prediction cache corresponding to the reference data file. Please see the NLP Prediction Cache Data Format reference for a description of supported file format.

• eval_path: string or null, default = null

  Path to prediction cache corresponding to the evaluation data file. Please see the NLP Prediction Cache Data Format reference for a description of supported file format.

• n_samples: int or null, default = null

  Number of samples from each dataset to score. If both ref_path and eval_path are specified, this must be set to null. If either prediction cache is not specified and n_samples is set to null, the default is to score the entire dataset. If model throughput is low, it is recommended to use a prediction cache or specify a smaller value for n_samples.