feat(script): add name and description parameters to GGUF converter

scripts/convert_to_gguf.py

@@ -219,6 +219,8 @@ def convert(
     output_path: str,
     config_path: str,
     dtype: str = "fp32",
+    name: str = None,
+    description: str = None,
 ):
     """
     Convert PyTorch checkpoint to GGUF format.
@@ -253,8 +255,10 @@ def convert(
     print("Writing metadata...")
 
     # General metadata
-    gguf_writer.add_name("Mel-Band-Roformer Vocal Separator")
-    gguf_writer.add_description("Audio source separation model for vocal extraction")
+    model_name = name if name else "Mel-Band-Roformer Separator"
+    model_description = description if description else "Music source separation model"
+    gguf_writer.add_name(model_name)
+    gguf_writer.add_description(model_description)
 
     # Determine types
     target_qtype = get_target_quantization_type(dtype)
@@ -464,6 +468,18 @@ Examples:
         ],
         help="Target quantization type. Norms/Biases will be kept as F32. (K-Quants not supported due to dim=384)",
     )
+    parser.add_argument(
+        "--name",
+        type=str,
+        default=None,
+        help="Model name (default: 'Mel-Band-Roformer Vocal Separator')",
+    )
+    parser.add_argument(
+        "--description",
+        type=str,
+        default=None,
+        help="Model description (default: 'Audio source separation model for vocal extraction')",
+    )
     args = parser.parse_args()
 
-    convert(args.ckpt, args.out, args.config, args.dtype)
+    convert(args.ckpt, args.out, args.config, args.dtype, args.name, args.description)