Update README.md

README.md

@@ -226,14 +226,14 @@ After training (or using pre-trained weights), extract features using [`extract_
 ```bash
 accelerate launch extract_clamp3.py --epoch <epoch> <input_dir> <output_dir> [--get_global]
 ```
-- **`--epoch <epoch>`:** (Optional) Specify the checkpoint epoch.
-- **`<input_dir>`:** Directory containing the input files.
-- **`<output_dir>`:** Destination folder for the output `.npy` features.
-- **`--get_global`**: (Optional) Flag to extract a global semantic vector for each input.
+- **`--epoch <epoch>`:** (Optional) Specify the checkpoint epoch.  
+- **`<input_dir>`:** Directory containing the input files.  
+- **`<output_dir>`:** Destination folder for the output `.npy` features.  
+- **`--get_global`**: **(Required for retrieval!)** Extracts a **global semantic vector** for each input.  
 
 All extracted features are stored as `.npy` files.
 
-> **Note**: In this project, we use the global semantic vectors (via average pooling and a linear layer) for both classification and retrieval tasks.
+> **Note**: For retrieval, `--get_global` must be used. Without it, CLaMP 3 will not work correctly for retrieval tasks. You only omit `--get_global` if you are performing downstream fine-tuning or need raw feature extraction for custom tasks.
 
 ### **Retrieval and Classification**
 #### **1. Semantic Search**