pypi huggingface-hub 0.7.0
v0.7.0: Repocard metadata

latest releases: 0.22.2, 0.22.1, 0.22.0...
23 months ago

Repocard metadata

This PR adds a metadata_update function that allows the user to update the metadata in a repository on the hub. The function accepts a dict with metadata (following the same pattern as the YAML in the README) and behaves as follows for all top level fields except model-index.

Examples:

Starting from

existing_results = [{
    'dataset': {'name': 'IMDb', 'type': 'imdb'},
    'metrics': [{'name': 'Accuracy', 'type': 'accuracy', 'value': 0.995}],
     'task': {'name': 'Text Classification', 'type': 'text-classification'}
}]

1. Overwrite existing metric value in existing result

new_results = deepcopy(existing_results)
new_results[0]["metrics"][0]["value"] = 0.999
_update_metadata_model_index(existing_results, new_results, overwrite=True)
[{'dataset': {'name': 'IMDb', 'type': 'imdb'},
  'metrics': [{'name': 'Accuracy', 'type': 'accuracy', 'value': 0.999}],
  'task': {'name': 'Text Classification', 'type': 'text-classification'}}]

2. Add new metric to existing result

new_results = deepcopy(existing_results)
new_results[0]["metrics"][0]["name"] = "Recall"
new_results[0]["metrics"][0]["type"] = "recall"
[{'dataset': {'name': 'IMDb', 'type': 'imdb'},
  'metrics': [{'name': 'Accuracy', 'type': 'accuracy', 'value': 0.995},
              {'name': 'Recall', 'type': 'recall', 'value': 0.995}],
  'task': {'name': 'Text Classification', 'type': 'text-classification'}}]

3. Add new result

new_results = deepcopy(existing_results)
new_results[0]["dataset"] = {'name': 'IMDb-2', 'type': 'imdb_2'}
[{'dataset': {'name': 'IMDb', 'type': 'imdb'},
  'metrics': [{'name': 'Accuracy', 'type': 'accuracy', 'value': 0.995}],
  'task': {'name': 'Text Classification', 'type': 'text-classification'}},
 {'dataset': ({'name': 'IMDb-2', 'type': 'imdb_2'},),
  'metrics': [{'name': 'Accuracy', 'type': 'accuracy', 'value': 0.995}],
  'task': {'name': 'Text Classification', 'type': 'text-classification'}}]

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