# tfma.load_eval_results

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| [![](https://www.tensorflow.org/images/GitHub-Mark-32px.png) View source on GitHub](https://github.com/tensorflow/model-analysis/blob/v0.46.0/tensorflow_model_analysis/api/model_eval_lib.py#L268-L300) |

Loads results for multiple models or multiple data sets.

    tfma.load_eval_results(
        output_paths: Union[str, List[str]],
        output_file_format: Optional[str] = 'tfrecord',
        mode: str = constants.MODEL_CENTRIC_MODE,
        model_name: Optional[str] = None
    ) -> view_types.EvalResults

### Used in the notebooks

| Used in the tutorials |
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| - [TensorFlow Model Analysis](https://www.tensorflow.org/tfx/tutorials/model_analysis/tfma_basic) |

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| ## Args ||
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| `output_paths` | A single path or list of output paths of completed tfma runs. |
| `output_file_format` | Optional file extension to filter files by. |
| `mode` | The mode of the evaluation. Currently, tfma.DATA_CENTRIC_MODE and tfma.MODEL_CENTRIC_MODE are supported. |
| `model_name` | Filters to only return results for given model. If unset all models are returned. |

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| ## Returns ||
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| An EvalResults containing the evaluation results serialized at output_paths. This can be used to construct a time series view. ||

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