Methods for using the Hugging Face Hub:
( model_id: str task_type: str dataset_type: str dataset_name: str metric_type: str metric_name: str metric_value: float task_name: str = None dataset_config: str = None dataset_split: str = None dataset_revision: str = None dataset_args: typing.Dict[str, int] = None metric_config: str = None metric_args: typing.Dict[str, int] = None overwrite: bool = False )
Parameters
str
) —
Model id from https://hf.co/models.
str
) —
Task id, refer to the Hub allowed tasks for allowed values.
str
) —
Dataset id from https://hf.co/datasets.
str
) —
Pretty name for the dataset.
str
) —
Metric id from https://hf.co/metrics.
str
) —
Pretty name for the metric.
float
) —
Computed metric value.
str
, optional) —
Pretty name for the task.
str
, optional) —
Dataset configuration used in load_dataset.
See load_dataset for more info.
str
, optional) —
Name of split used for metric computation.
str
, optional) —
Git hash for the specific version of the dataset.
dict[str, int]
, optional) —
Additional arguments passed to load_dataset.
str
, optional) —
Configuration for the metric (e.g. the GLUE metric has a configuration for each subset).
dict[str, int]
, optional) —
Arguments passed during compute().
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.
Pushes the result of a metric to the metadata of a model repository in the Hub.