Upload configuration.py

configuration.py

@@ -0,0 +1,51 @@
+from transformers import PretrainedConfig
+
+class MoEGPTConfig(PretrainedConfig):
+    model_type = "moegpt"
+
+    def __init__(
+        self,
+        vocab_size=50304,
+        n_embd=1152, #768,
+        n_layer=24,#12,
+        n_head=16,#12,
+        sequence_length=1024,
+        moe=False,
+        moe_routing="standard_gating",
+        moe_num_experts=4,
+        moe_num_experts_per_tok=2,
+        moe_softmax_order="softmax_topk",
+        moe_router_loss="load_balancing_z_loss",
+        moe_aux_loss_factor=0.01,
+        moe_z_loss_factor=1.0,
+        mlp_dim_exp_factor=1.0,
+        dropout=0.0,
+        bias=False,
+        architectures=["MoEGPTForCausalLM"],
+        auto_map={
+            "AutoConfig": "configuration.MoEGPTConfig",
+            "AutoModelForCausalLM": "modeling.MoEGPTForCausalLM",
+            "AutoTokenizer": "GPT2TokenizerFast"
+        },
+        **kwargs,
+    ):
+        super().__init__(**kwargs)
+        self.vocab_size = vocab_size
+        self.n_embd = n_embd
+        self.n_layer = n_layer
+        self.n_head = n_head
+        self.sequence_length = sequence_length
+        self.moe = moe
+        self.moe_routing = moe_routing
+        self.moe_num_experts = moe_num_experts
+        self.moe_num_experts_per_tok = moe_num_experts_per_tok
+        self.moe_softmax_order = moe_softmax_order
+        self.moe_router_loss = moe_router_loss
+        self.moe_aux_loss_factor = moe_aux_loss_factor
+        self.moe_z_loss_factor = moe_z_loss_factor
+        self.mlp_dim_exp_factor = mlp_dim_exp_factor
+        self.dropout = dropout
+        self.bias = bias
+        self.architectures = architectures
+        self.auto_map = auto_map
+