diff --git a/examples/convert_jax_model_to_pytorch.py b/examples/convert_jax_model_to_pytorch.py
index 632c0b8782..d90c7cd5e9 100644
--- a/examples/convert_jax_model_to_pytorch.py
+++ b/examples/convert_jax_model_to_pytorch.py
@@ -9,11 +9,9 @@
 Usage:
     # Just inspect keys:
     python examples/convert_jax_model_to_pytorch.py --checkpoint_dir /path/to/checkpoint --inspect_only
-    python examples/convert_jax_model_to_pytorch.py --checkpoint_dir /path/to/checkpoint --inspect_only
 
     # Convert to PyTorch:
     python examples/convert_jax_model_to_pytorch.py --checkpoint_dir /path/to/checkpoint --output_path /path/to/output
-    python examples/convert_jax_model_to_pytorch.py --checkpoint_dir /path/to/checkpoint --output_path /path/to/output
 
 Example:
     # pi0_droid
@@ -44,7 +42,6 @@
 import openpi.models.pi0_config
 import openpi.models_pytorch.pi0_pytorch
 from openpi.training import utils
-import openpi.training.config as _config
 
 
 def slice_paligemma_state_dict(state_dict, config):
@@ -419,9 +416,7 @@ def load_jax_model_and_print_keys(checkpoint_dir: str):
     print(utils.array_tree_to_info(metadata))
 
 
-def convert_pi0_checkpoint(
-    checkpoint_dir: str, precision: str, output_path: str, model_config: openpi.models.pi0_config.Pi0Config
-):
+def convert_pi0_checkpoint(checkpoint_dir: str, precision: str, output_path: str):
     """
     Convert PI0 JAX checkpoint to PyTorch format.
 
@@ -429,14 +424,25 @@ def convert_pi0_checkpoint(
         checkpoint_dir: Path to the JAX checkpoint
         precision: Model precision (float32, bfloat16, float16)
         output_path: Path to save the converted PyTorch model
-        model_config: Model config
     """
     print(f"Converting PI0 checkpoint from {checkpoint_dir} to {output_path}")
-    print(f"Model config: {model_config}")
 
     # Break down orbax ckpts by restoring via JAX to respect dtype
     initial_params = slice_initial_orbax_checkpoint(checkpoint_dir=checkpoint_dir, restore_precision="float32")
 
+    # Detect pi05 from checkpoint contents: pi05 uses time_mlp_in/out instead of state_proj
+    is_pi05 = "time_mlp_in" in initial_params["projection_params"]
+    print(f"Auto-detected model type: {'Pi0.5' if is_pi05 else 'Pi0'}")
+
+    # Infer action_dim from action_in_proj kernel shape: [action_dim, expert_hidden_size]
+    action_in_proj_kernel = initial_params["projection_params"]["action_in_proj"]["kernel"]
+    if isinstance(action_in_proj_kernel, dict):
+        action_in_proj_kernel = action_in_proj_kernel["value"]
+    action_dim = action_in_proj_kernel.shape[0]
+    print(f"Auto-detected action_dim: {action_dim}")
+
+    model_config = openpi.models.pi0_config.Pi0Config(pi05=is_pi05, action_dim=action_dim)
+
     # Process projection params
     if model_config.pi05:
         keys = [
@@ -557,7 +563,6 @@ def __init__(self):
 
 def main(
     checkpoint_dir: str,
-    config_name: str,
     output_path: str | None = None,
     precision: Literal["float32", "bfloat16", "float16"] = "bfloat16",
     *,
@@ -571,16 +576,13 @@ def main(
         precision: Precision for model conversion
         inspect_only: Only inspect parameter keys, don't convert
     """
-    model_config = _config.get_config(config_name).model
-    if not isinstance(model_config, openpi.models.pi0_config.Pi0Config):
-        raise ValueError(f"Config {config_name} is not a Pi0Config")
     if inspect_only:
         load_jax_model_and_print_keys(checkpoint_dir)
     else:
         if not output_path:
             print("Error: --output_path is required for conversion. Use --inspect_only to only view keys.")
             return
-        convert_pi0_checkpoint(checkpoint_dir, precision, output_path, model_config)
+        convert_pi0_checkpoint(checkpoint_dir, precision, output_path)
 
 
 if __name__ == "__main__":