src/transformers/models/videomae/convert_videomae_to_pytorch.py/get_videomae_config
def get_videomae_config(model_name):
    config = VideoMAEConfig()

    if "large" in model_name:
        config.hidden_size = 1024
        config.intermediate_size = 4096
        config.num_hidden_layers = 24
        config.num_attention_heads = 16
        config.decoder_num_hidden_layers = 12
        config.decoder_num_attention_heads = 8
        config.decoder_hidden_size = 512
        config.decoder_intermediate_size = 2048

    if "finetuned" not in model_name:
        config.use_mean_pooling = False

    if "finetuned" in model_name:
        repo_id = "huggingface/label-files"
        if "kinetics" in model_name:
            config.num_labels = 400
            filename = "kinetics400-id2label.json"
        elif "ssv2" in model_name:
            config.num_labels = 174
            filename = "something-something-v2-id2label.json"
        else:
            raise ValueError("Model name should either contain 'kinetics' or 'ssv2' in case it's fine-tuned.")
        id2label = json.load(open(hf_hub_download(repo_id, filename, repo_type="dataset"), "r"))
        id2label = {int(k): v for k, v in id2label.items()}
        config.id2label = id2label
        config.label2id = {v: k for k, v in id2label.items()}

    return config