diff --git a/vall_e/config.py b/vall_e/config.py
index bf3d6c0..e455c05 100644
--- a/vall_e/config.py
+++ b/vall_e/config.py
@@ -37,11 +37,12 @@ class Config(ConfigBase):
     eval_every: int = 2_000
     save_ckpt_every: int = 10_000
 
-    model: str = "ar"
-    d_model: int = 512
-    n_heads: int = 8
-    n_layers: int = 12
-    p_dropout: float = 0.1
+    model: str = "ar-quarter"
+    spkr_name_getter: str = "lambda p: p.parts[-2]"
+
+    @cached_property
+    def get_spkr(self):
+        return eval(self.spkr_name_getter)
 
     @property
     def ds_cfg(self):
diff --git a/vall_e/train.py b/vall_e/train.py
index a5a721f..e262ed1 100644
--- a/vall_e/train.py
+++ b/vall_e/train.py
@@ -9,30 +9,13 @@ from .config import cfg
 from .data import create_train_val_dataloader
 from .emb import qnt
 from .utils import setup_logging, to_device, trainer
-from .vall_e import AR, NAR
+from .vall_e import get_model
 
 _logger = logging.getLogger(__name__)
 
 
 def load_engines():
-    if cfg.model.lower() == "ar":
-        model = AR(
-            cfg.num_tokens,
-            cfg.d_model,
-            cfg.n_heads,
-            cfg.n_layers,
-            cfg.p_dropout,
-        )
-    elif cfg.model.lower() == "nar":
-        model = NAR(
-            cfg.num_tokens,
-            cfg.d_model,
-            cfg.n_heads,
-            cfg.n_layers,
-            cfg.p_dropout,
-        )
-    else:
-        raise NotImplementedError(cfg.model)
+    model = get_model(cfg.model)
 
     engines = dict(
         model=trainer.Engine(
diff --git a/vall_e/vall_e/__init__.py b/vall_e/vall_e/__init__.py
index ab095f0..2bf8126 100644
--- a/vall_e/vall_e/__init__.py
+++ b/vall_e/vall_e/__init__.py
@@ -1,2 +1,40 @@
+from ..config import cfg
 from .ar import AR
 from .nar import NAR
+
+
+def get_model(name):
+    name = name.lower()
+
+    if name.startswith("ar"):
+        Model = AR
+    elif str().startswith("nar"):
+        Model = NAR
+    else:
+        raise ValueError("Model name should start with AR or NAR.")
+
+    if "-quarter" in name:
+        model = Model(
+            cfg.num_tokens,
+            d_model=256,
+            n_heads=4,
+            n_layers=12,
+        )
+    elif "-half" in name:
+        model = Model(
+            cfg.num_tokens,
+            d_model=512,
+            n_heads=8,
+            n_layers=12,
+        )
+    elif "-official" in name:
+        model = Model(
+            cfg.num_tokens,
+            d_model=1024,
+            n_heads=16,
+            n_layers=12,
+        )
+    else:
+        raise NotImplementedError(name)
+
+    return model