src/transformers/models/hubert/modeling_hubert.py/HubertForSequenceClassification/__init__
class HubertForSequenceClassification:    def __init__(self, config):
        super().__init__(config)

        self.hubert = HubertModel(config)
        num_layers = config.num_hidden_layers + 1  # transformer layers + input embeddings
        if config.use_weighted_layer_sum:
            self.layer_weights = nn.Parameter(torch.ones(num_layers) / num_layers)
        self.projector = nn.Linear(config.hidden_size, config.classifier_proj_size)
        self.classifier = nn.Linear(config.classifier_proj_size, config.num_labels)

        self.init_weights()