Update README.md

README.md

@@ -34,21 +34,21 @@ Here's an example of how to use the RDT-1B model for inference on a Mobile-ALOHA
 ```python
 # Clone the repository and install dependencies
 from scripts.agilex_model import create_model
-CAMERA_NAMES = ['cam_high', 'cam_right_wrist', 'cam_left_wrist'] # Names of cameras used for visual input
+# Names of cameras used for visual input
+CAMERA_NAMES = ['cam_high', 'cam_right_wrist', 'cam_left_wrist']
 config = {
     'episode_len': 1000,  # Max length of one episode
     'state_dim': 14,      # Dimension of the robot's state
     'chunk_size': 64,     # Number of actions to predict in one step
     'camera_names': CAMERA_NAMES,
 }
-control_frequency=25 
 pretrained_vision_encoder_name_or_path = "google/siglip-so400m-patch14-384" 
 # Create the model with specified configuration
 model = create_model(
     args=config,
     dtype=torch.bfloat16, 
     pretrained_vision_encoder_name_or_path=pretrained_vision_encoder_name_or_path,
-    control_frequency=control_frequency,
+    control_frequency=25,
 )
 # Start inference process
 # Load pre-computed language embeddings