src/transformers/models/albert/configuration_albert.py/AlbertConfig/__init__
class AlbertConfig:    def __init__(
        self,
        vocab_size=30000,
        embedding_size=128,
        hidden_size=4096,
        num_hidden_layers=12,
        num_hidden_groups=1,
        num_attention_heads=64,
        intermediate_size=16384,
        inner_group_num=1,
        hidden_act="gelu_new",
        hidden_dropout_prob=0,
        attention_probs_dropout_prob=0,
        max_position_embeddings=512,
        type_vocab_size=2,
        initializer_range=0.02,
        layer_norm_eps=1e-12,
        classifier_dropout_prob=0.1,
        position_embedding_type="absolute",
        pad_token_id=0,
        bos_token_id=2,
        eos_token_id=3,
        **kwargs,
    ):
        super().__init__(pad_token_id=pad_token_id, bos_token_id=bos_token_id, eos_token_id=eos_token_id, **kwargs)

        self.vocab_size = vocab_size
        self.embedding_size = embedding_size
        self.hidden_size = hidden_size
        self.num_hidden_layers = num_hidden_layers
        self.num_hidden_groups = num_hidden_groups
        self.num_attention_heads = num_attention_heads
        self.inner_group_num = inner_group_num
        self.hidden_act = hidden_act
        self.intermediate_size = intermediate_size
        self.hidden_dropout_prob = hidden_dropout_prob
        self.attention_probs_dropout_prob = attention_probs_dropout_prob
        self.max_position_embeddings = max_position_embeddings
        self.type_vocab_size = type_vocab_size
        self.initializer_range = initializer_range
        self.layer_norm_eps = layer_norm_eps
        self.classifier_dropout_prob = classifier_dropout_prob
        self.position_embedding_type = position_embedding_type