src/transformers/models/efficientnet/convert_efficientnet_to_pytorch.py/get_efficientnet_config
def get_efficientnet_config(model_name):
    config = EfficientNetConfig()
    config.hidden_dim = CONFIG_MAP[model_name]["hidden_dim"]
    config.width_coefficient = CONFIG_MAP[model_name]["width_coef"]
    config.depth_coefficient = CONFIG_MAP[model_name]["depth_coef"]
    config.image_size = CONFIG_MAP[model_name]["image_size"]
    config.dropout_rate = CONFIG_MAP[model_name]["dropout_rate"]
    config.depthwise_padding = CONFIG_MAP[model_name]["dw_padding"]

    repo_id = "huggingface/label-files"
    filename = "imagenet-1k-id2label.json"
    config.num_labels = 1000
    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