--- # Example metadata to be added to a model card. language: - {lang_0} # Example: fr - {lang_1} # Example: en license: {license} # Example: apache-2.0 or any license from https://hf.co/docs/hub/repositories-licenses license_name: {license_name} # If license = other (license not in https://hf.co/docs/hub/repositories-licenses), specify an id for it here, like `my-license-1.0`. license_link: {license_link} # If license = other, specify "LICENSE" or "LICENSE.md" to link to a file of that name inside the repo, or a URL to a remote file. library_name: {library_name} # Optional. Example: keras or any library from https://github.com/huggingface/huggingface.js/blob/main/packages/tasks/src/model-libraries.ts tags: - {tag_0} # Example: audio - {tag_1} # Example: automatic-speech-recognition - {tag_2} # Example: speech - {tag_3} # Example to specify a library: allennlp datasets: - {dataset_0} # Example: common_voice. Use dataset id from https://hf.co/datasets buckets: - {bucket_0} # Example: my-org/my-bucket metrics: - {metric_0} # Example: wer. Use metric id from https://hf.co/metrics base_model: {base_model} # Example: stabilityai/stable-diffusion-xl-base-1.0. Can also be a list (for merges) # Optional. Add this if you want to encode your eval results in a structured way. # There is a newer, simpler version of this metadata format in ./eval_results.yaml model-index: - name: {model_id} results: - task: type: {task_type} # Required. Example: automatic-speech-recognition name: {task_name} # Optional. Example: Speech Recognition dataset: type: {dataset_type} # Required. Example: common_voice. Use dataset id from https://hf.co/datasets name: {dataset_name} # Required. A pretty name for the dataset. Example: Common Voice (French) config: {dataset_config} # Optional. The name of the dataset subset used in `load_dataset()`. Example: fr in `load_dataset("common_voice", "fr")`. See the `datasets` docs for more info: https://huggingface.co/docs/datasets/package_reference/loading_methods#datasets.load_dataset.name split: {dataset_split} # Optional. Example: test revision: {dataset_revision} # Optional. Example: 5503434ddd753f426f4b38109466949a1217c2bb args: {arg_0}: {value_0} # Optional. Additional arguments to `load_dataset()`. Example for wikipedia: language: en {arg_1}: {value_1} # Optional. Example for wikipedia: date: 20220301 metrics: - type: {metric_type} # Required. Example: wer. Use metric id from https://hf.co/metrics value: {metric_value} # Required. Example: 20.90 name: {metric_name} # Optional. Example: Test WER config: {metric_config} # Optional. The name of the metric configuration used in `load_metric()`. Example: bleurt-large-512 in `load_metric("bleurt", "bleurt-large-512")`. See the `datasets` docs for more info: https://huggingface.co/docs/datasets/main/en/loading args: {arg_0}: {value_0} # Optional. The arguments passed during `Metric.compute()`. Example for `bleu`: max_order: 4 verifyToken: {verify_token} # Optional. If present, this is a signature that can be used to prove that evaluation was generated by Hugging Face (vs. self-reported). source: # Optional. The source for this result. name: {source_name} # Optional. The name of the source. Example: Open LLM Leaderboard. url: {source_url} # Required if source is provided. A link to the source. Example: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard. --- This markdown file contains the spec for the modelcard metadata. Properties will be validated by the Hub when git pushing changes to your README.md file. Valid license identifiers can be found in [our docs](https://huggingface.co/docs/hub/repositories-licenses). For a template for the human-readable portion of the model card, see: [modelcard_template.md file](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/modelcard_template.md).