diff --git a/invokeai/backend/model_management/models/controlnet.py b/invokeai/backend/model_management/models/controlnet.py
index d75c55010a..687afbffbd 100644
--- a/invokeai/backend/model_management/models/controlnet.py
+++ b/invokeai/backend/model_management/models/controlnet.py
@@ -18,7 +18,7 @@ class ControlNetModel(ModelBase):
     #model_class: Type
     #model_size: int
 
-    class Config(ModelConfigBase):
+    class ControlNetModelConfig(ModelConfigBase):
         format: Union[Literal["checkpoint"], Literal["diffusers"]]
 
     def __init__(self, model_path: str, base_model: BaseModelType, model_type: ModelType):
@@ -82,6 +82,6 @@ class ControlNetModel(ModelBase):
         base_model: BaseModelType,
     ) -> str:
         if cls.detect_format(model_path) != "diffusers":
-            raise NotImlemetedError("Checkpoint controlnet models currently unsupported")
+            raise NotImplementedError("Checkpoint controlnet models currently unsupported")
         else:
             return model_path
diff --git a/invokeai/backend/model_management/models/lora.py b/invokeai/backend/model_management/models/lora.py
index bcf3224ece..60865817b9 100644
--- a/invokeai/backend/model_management/models/lora.py
+++ b/invokeai/backend/model_management/models/lora.py
@@ -15,7 +15,7 @@ from ..lora import LoRAModel as LoRAModelRaw
 class LoRAModel(ModelBase):
     #model_size: int
 
-    class Config(ModelConfigBase):
+    class LoraModelConfig(ModelConfigBase):
         format: Union[Literal["lycoris"], Literal["diffusers"]]
 
     def __init__(self, model_path: str, base_model: BaseModelType, model_type: ModelType):
diff --git a/invokeai/backend/model_management/models/stable_diffusion.py b/invokeai/backend/model_management/models/stable_diffusion.py
index bd519c88c8..9856069ea5 100644
--- a/invokeai/backend/model_management/models/stable_diffusion.py
+++ b/invokeai/backend/model_management/models/stable_diffusion.py
@@ -22,12 +22,12 @@ from omegaconf import OmegaConf
 
 class StableDiffusion1Model(DiffusersModel):
 
-    class DiffusersConfig(ModelConfigBase):
+    class StableDiffusion1DiffusersModelConfig(ModelConfigBase):
         format: Literal["diffusers"]
         vae: Optional[str] = Field(None)
         variant: ModelVariantType
 
-    class CheckpointConfig(ModelConfigBase):
+    class StableDiffusion1CheckpointModelConfig(ModelConfigBase):
         format: Literal["checkpoint"]
         vae: Optional[str] = Field(None)
         config: Optional[str] = Field(None)
@@ -107,7 +107,7 @@ class StableDiffusion1Model(DiffusersModel):
     ) -> str:
         assert model_path == config.path
 
-        if isinstance(config, cls.CheckpointConfig):
+        if isinstance(config, cls.CheckpointModelConfig):
             return _convert_ckpt_and_cache(
                 version=BaseModelType.StableDiffusion1,
                 model_config=config,
@@ -120,14 +120,14 @@ class StableDiffusion1Model(DiffusersModel):
 class StableDiffusion2Model(DiffusersModel):
 
     # TODO: check that configs overwriten properly
-    class DiffusersConfig(ModelConfigBase):
+    class StableDiffusion2DiffusersModelConfig(ModelConfigBase):
         format: Literal["diffusers"]
         vae: Optional[str] = Field(None)
         variant: ModelVariantType
         prediction_type: SchedulerPredictionType
         upcast_attention: bool
 
-    class CheckpointConfig(ModelConfigBase):
+    class StableDiffusion2CheckpointModelConfig(ModelConfigBase):
         format: Literal["checkpoint"]
         vae: Optional[str] = Field(None)
         config: Optional[str] = Field(None)
@@ -220,7 +220,7 @@ class StableDiffusion2Model(DiffusersModel):
     ) -> str:
         assert model_path == config.path
 
-        if isinstance(config, cls.CheckpointConfig):
+        if isinstance(config, cls.CheckpointModelConfig):
             return _convert_ckpt_and_cache(
                 version=BaseModelType.StableDiffusion2,
                 model_config=config,
@@ -256,7 +256,7 @@ def _select_ckpt_config(version: BaseModelType, variant: ModelVariantType):
 # TODO: rework
 def _convert_ckpt_and_cache(
     version: BaseModelType,
-    model_config: Union[StableDiffusion1Model.CheckpointConfig, StableDiffusion2Model.CheckpointConfig],
+    model_config: Union[StableDiffusion1Model.StableDiffusion1CheckpointModelConfig, StableDiffusion2Model.StableDiffusion2CheckpointModelConfig],
     output_path: str,
 ) -> str:
     """
@@ -281,8 +281,8 @@ def _convert_ckpt_and_cache(
         prediction_type = SchedulerPredictionType.Epsilon
 
     elif version == BaseModelType.StableDiffusion2:
-        upcast_attention = config.upcast_attention
-        prediction_type = config.prediction_type
+        upcast_attention = model_config.upcast_attention
+        prediction_type = model_config.prediction_type
 
     else:
         raise Exception(f"Unknown model provided: {version}")
diff --git a/invokeai/backend/model_management/models/textual_inversion.py b/invokeai/backend/model_management/models/textual_inversion.py
index e8c96ff31e..0ed19e0b92 100644
--- a/invokeai/backend/model_management/models/textual_inversion.py
+++ b/invokeai/backend/model_management/models/textual_inversion.py
@@ -14,7 +14,7 @@ from ..lora import TextualInversionModel as TextualInversionModelRaw
 class TextualInversionModel(ModelBase):
     #model_size: int
 
-    class Config(ModelConfigBase):
+    class TextualInversionModelConfig(ModelConfigBase):
         format: None
 
     def __init__(self, model_path: str, base_model: BaseModelType, model_type: ModelType):
diff --git a/invokeai/backend/model_management/models/vae.py b/invokeai/backend/model_management/models/vae.py
index 1edb57ccc4..f285648323 100644
--- a/invokeai/backend/model_management/models/vae.py
+++ b/invokeai/backend/model_management/models/vae.py
@@ -1,5 +1,6 @@
 import os
 import torch
+import safetensors
 from pathlib import Path
 from typing import Optional, Union, Literal
 from .base import (
@@ -22,7 +23,7 @@ class VaeModel(ModelBase):
     #vae_class: Type
     #model_size: int
 
-    class Config(ModelConfigBase):
+    class VAEModelConfig(ModelConfigBase):
         format: Union[Literal["checkpoint"], Literal["diffusers"]]
 
     def __init__(self, model_path: str, base_model: BaseModelType, model_type: ModelType):