def write_model_card(
    hf_model_name: str,
    repo_root=DEFAULT_REPO,
    save_dir=Path("marian_converted"),
    dry_run=False,
    extra_metadata={},
) -> str:
    """
    Copy the most recent model's readme section from opus, and add metadata. upload command: aws s3 sync model_card_dir
    s3://models.huggingface.co/bert/Helsinki-NLP/ --dryrun
    """
    import pandas as pd

    hf_model_name = remove_prefix(hf_model_name, ORG_NAME)
    opus_name: str = convert_hf_name_to_opus_name(hf_model_name)
    if repo_root not in ("OPUS-MT-train", "Tatoeba-Challenge"):
        raise ValueError(f"Repos root is {repo_root}. Expected either OPUS-MT-train or Tatoeba-Challenge")
    opus_readme_path = Path(repo_root).joinpath("models", opus_name, "README.md")
    if not (opus_readme_path.exists()):
        raise ValueError(f"Readme file {opus_readme_path} not found")

    opus_src, opus_tgt = [x.split("+") for x in opus_name.split("-")]

    readme_url = f"https://github.com/Helsinki-NLP/{repo_root}/tree/master/models/{opus_name}/README.md"

    s, t = ",".join(opus_src), ",".join(opus_tgt)
    metadata = {
        "hf_name": hf_model_name,
        "source_languages": s,
        "target_languages": t,
        "opus_readme_url": readme_url,
        "original_repo": repo_root,
        "tags": ["translation"],
    }
    metadata.update(extra_metadata)
    metadata.update(get_system_metadata(repo_root))

    # combine with opus markdown

    extra_markdown = (
        f"### {hf_model_name}\n\n* source group: {metadata['src_name']} \n* target group: "
        f"{metadata['tgt_name']} \n*  OPUS readme: [{opus_name}]({readme_url})\n"
    )

    content = opus_readme_path.open().read()
    content = content.split("\n# ")[-1]  # Get the lowest level 1 header in the README -- the most recent model.
    splat = content.split("*")[2:]
    print(splat[3])
    content = "*".join(splat)
    content = (
        FRONT_MATTER_TEMPLATE.format(metadata["src_alpha2"])
        + extra_markdown
        + "\n* "
        + content.replace("download", "download original weights")
    )

    items = "\n\n".join([f"- {k}: {v}" for k, v in metadata.items()])
    sec3 = "\n### System Info: \n" + items
    content += sec3
    if dry_run:
        return content, metadata
    sub_dir = save_dir / f"opus-mt-{hf_model_name}"
    sub_dir.mkdir(exist_ok=True)
    dest = sub_dir / "README.md"
    dest.open("w").write(content)
    pd.Series(metadata).to_json(sub_dir / "metadata.json")

    # if dry_run:
    return content, metadata

    Copy the most recent model's readme section from opus, and add metadata. upload command: aws s3 sync model_card_dir
    s3://models.huggingface.co/bert/Helsinki-NLP/ --dryrun
    
dpkd/transformers/src/transformers/models/marian/convert_marian_to_pytorch.py