Use optimal alignment heads in Whisper conversion

whisper/convert.py

@@ -59,6 +59,19 @@
 }
 
 
+def _get_model_variant(name_or_path: str) -> str | None:
+    """Extract model variant for alignment heads lookup."""
+    if name_or_path in _ALIGNMENT_HEADS:
+        return name_or_path
+
+    # Extract from repo name like "openai/whisper-large-v3"
+    name = name_or_path.split("/")[-1]
+    if name.startswith("whisper-"):
+        return name[8:]  # Remove "whisper-" prefix
+
+    return None
+
+
 def _download(url: str, root: str) -> str:
     os.makedirs(root, exist_ok=True)
 
@@ -156,10 +169,11 @@ def load_torch_weights_and_config(
     if download_root is None:
         download_root = os.path.join(os.path.expanduser("~"), ".cache/whisper")
 
-    # todo: accept alignment_heads of local Pytorch checkpoint
-    alignment_heads = None
+    # Look up alignment heads using normalized variant name
+    variant = _get_model_variant(name_or_path)
+    alignment_heads = _ALIGNMENT_HEADS.get(variant) if variant else None
+
     if name_or_path in _MODELS:
-        alignment_heads = _ALIGNMENT_HEADS[name_or_path]
         name_or_path = _download(_MODELS[name_or_path], download_root)
     elif not Path(name_or_path).exists():
         # Try downloading from HF