evaluate/main/en/package_reference/hub_methods.md

# Hub methods

Methods for using the Hugging Face Hub:

## Push to hub [[evaluate.push_to_hub]]

#### evaluate.push_to_hub[[evaluate.push_to_hub]]

[Source](https://github.com/huggingface/evaluate/blob/main/src/evaluate/hub.py#L14)

Pushes the result of a metric to the metadata of a model repository in the Hub.

Example:

```python
>>> push_to_hub(
...     model_id="huggingface/gpt2-wikitext2",
...     metric_value=0.5
...     metric_type="bleu",
...     metric_name="BLEU",
...     dataset_name="WikiText",
...     dataset_type="wikitext",
...     dataset_split="test",
...     task_type="text-generation",
...     task_name="Text Generation"
... )
```

**Parameters:**

model_id (`str`) : Model id from https://hf.co/models.

task_type (`str`) : Task id, refer to the [Hub allowed tasks](https://github.com/huggingface/evaluate/blob/main/src/evaluate/config.py#L154) for allowed values.

dataset_type (`str`) : Dataset id from https://hf.co/datasets.

dataset_name (`str`) : Pretty name for the dataset.

metric_type (`str`) : Metric id from https://hf.co/metrics.

metric_name (`str`) : Pretty name for the metric.

metric_value (`float`) : Computed metric value.

task_name (`str`, *optional*) : Pretty name for the task.

dataset_config (`str`, *optional*) : Dataset configuration used in [load_dataset](https://huggingface.co/docs/datasets/main/en/package_reference/loading_methods#datasets.load_dataset). See [load_dataset](https://huggingface.co/docs/datasets/main/en/package_reference/loading_methods#datasets.load_dataset) for more info.

dataset_split (`str`, *optional*) : Name of split used for metric computation.

dataset_revision (`str`, *optional*) : Git hash for the specific version of the dataset.

dataset_args (`dict[str, int]`, *optional*) : Additional arguments passed to [load_dataset](https://huggingface.co/docs/datasets/main/en/package_reference/loading_methods#datasets.load_dataset).

metric_config (`str`, *optional*) : Configuration for the metric (e.g. the GLUE metric has a configuration for each subset).

metric_args (`dict[str, int]`, *optional*) : Arguments passed during [compute()](/docs/evaluate/main/en/package_reference/main_classes#evaluate.EvaluationModule.compute).

overwrite (`bool`, *optional*, defaults to `False`) : If set to `True` an existing metric field can be overwritten, otherwise attempting to overwrite any existing fields will cause an error.