Delete configuration_bailing_moe_v2.py

configuration_bailing_moe_v2.py

@@ -1,84 +0,0 @@
-"""Bailing MoE V2 model configuration"""
-
-from transformers.configuration_utils import PretrainedConfig
-
-
-class BailingMoeV2Config(PretrainedConfig):
-
-    def __init__(
-        self,
-        vocab_size=157184,
-        hidden_size=2048,
-        intermediate_size=5120,
-        num_hidden_layers=20,
-        num_attention_heads=16,
-        num_key_value_heads=4,
-        hidden_act="silu",
-        use_qkv_bias=False,  # bailing only
-        use_bias=False,  # bailing only
-        rms_norm_eps=1e-06,
-        tie_word_embeddings=False,  # PretrainedConfig key, here change default value.
-        embedding_dropout=0.0,
-        attention_dropout=0.0,
-        output_dropout=0.0,
-        initializer_range=0.02,
-        max_position_embeddings=32768,
-        rope_theta=600000.0,
-        use_cache=True,
-        max_window_layers=20,
-        rope_scaling=None,
-        pad_token_id=156892,
-        eos_token_id=156892,
-        num_experts=256,
-        num_shared_experts=1,
-        num_experts_per_tok=8,
-        n_group=8,
-        topk_group=4,
-        moe_intermediate_size=512,
-        first_k_dense_replace=1,
-        head_dim=128,
-        output_router_logits=False,
-        use_qk_norm=True,
-        num_nextn_predict_layers=0,
-        mtp_loss_scaling_factor=0,
-        moe_router_enable_expert_bias=True,
-        routed_scaling_factor=1.0,
-        **kwargs,
-    ):
-        self.num_hidden_layers = num_hidden_layers
-        self.vocab_size = vocab_size
-        self.hidden_size = hidden_size
-        self.intermediate_size = intermediate_size
-        self.num_attention_heads = num_attention_heads
-        self.num_key_value_heads = num_key_value_heads
-        self.hidden_act = hidden_act
-        self.use_qkv_bias = use_qkv_bias
-        self.use_bias = use_bias
-        self.rms_norm_eps = rms_norm_eps
-        self.embedding_dropout = embedding_dropout
-        self.attention_dropout = attention_dropout
-        self.output_dropout = output_dropout
-        self.num_nextn_predict_layers = num_nextn_predict_layers
-        self.mtp_loss_scaling_factor = mtp_loss_scaling_factor
-        self.initializer_range = initializer_range
-        self.max_position_embeddings = max_position_embeddings
-        self.rope_theta = rope_theta
-        self.use_cache = use_cache
-        self.max_window_layers = max_window_layers
-        self.head_dim = head_dim or self.hidden_size // self.num_attention_heads
-        self.rope_scaling = rope_scaling
-        self.use_qk_norm = use_qk_norm
-        self.moe_router_enable_expert_bias = moe_router_enable_expert_bias
-        self.routed_scaling_factor = routed_scaling_factor
-
-        # MoE configs
-        self.num_experts = num_experts
-        self.num_shared_experts = num_shared_experts
-        self.num_experts_per_tok = num_experts_per_tok
-        self.n_group = n_group
-        self.topk_group = topk_group
-        self.moe_intermediate_size = moe_intermediate_size
-        self.first_k_dense_replace = first_k_dense_replace
-        self.output_router_logits = output_router_logits
-
-        super().__init__(pad_token_id=pad_token_id, eos_token_id=eos_token_id, tie_word_embeddings=tie_word_embeddings, **kwargs)