Remove redundant types, kwargs back in own section (lesser of many evils?)

Author: rwightman

timm/models/_factory.py

@@ -12,7 +12,7 @@
 __all__ = ['parse_model_name', 'safe_model_name', 'create_model']
 
 
-def parse_model_name(model_name):
+def parse_model_name(model_name: str):
     if model_name.startswith('hf_hub'):
         # NOTE for backwards compat, deprecate hf_hub use
         model_name = model_name.replace('hf_hub', 'hf-hub')
@@ -26,7 +26,7 @@ def parse_model_name(model_name):
         return 'timm', model_name
 
 
-def safe_model_name(model_name, remove_source=True):
+def safe_model_name(model_name: str, remove_source: bool = True):
     # return a filename / path safe model name
     def make_safe(name):
         return ''.join(c if c.isalnum() else '_' for c in name).rstrip('_')
@@ -56,16 +56,19 @@ def create_model(
     </Tip>
 
     Args:
-        model_name (`str`): Name of model to instantiate.
-        pretrained (`bool`): If set to `True`, load pretrained ImageNet-1k weights.
-        pretrained_cfg (`Union[str, dict, PretrainedCfg]`): Pass in an external pretrained_cfg for model.
-        pretrained_cfg_overlay (`dict`): Replace key-values in base pretrained_cfg with these.
-        checkpoint_path (`str`): Path of checkpoint to load _after_ the model is initialized.
-        scriptable (`bool`): Set layer config so that model is jit scriptable (not working for all models yet).
-        exportable (`bool`): Set layer config so that model is traceable / ONNX exportable (not fully impl/obeyed yet).
-        no_jit (`bool`): Set layer config so that model doesn't utilize jit scripted layers (so far activations only).
-        **drop_rate (`float`): Dropout rate for training. Defaults to `0.0`.
-        **global_pool (`str`): Global pooling type. Defaults to `'avg'`.
+        model_name: Name of model to instantiate.
+        pretrained: If set to `True`, load pretrained ImageNet-1k weights.
+        pretrained_cfg: Pass in an external pretrained_cfg for model.
+        pretrained_cfg_overlay: Replace key-values in base pretrained_cfg with these.
+        checkpoint_path: Path of checkpoint to load _after_ the model is initialized.
+        scriptable: Set layer config so that model is jit scriptable (not working for all models yet).
+        exportable: Set layer config so that model is traceable / ONNX exportable (not fully impl/obeyed yet).
+        no_jit: Set layer config so that model doesn't utilize jit scripted layers (so far activations only).
+
+    Keyword Args:
+        drop_rate (float): Classifier dropout rate for training.
+        drop_path_rate (float): Stochastic depth drop rate for training.
+        global_pool (str): Classifier global pooling type.
 
     Example: