Add script to convert TTS .bin weights to safetensors

Needed on this branch: qwen-asr upgrades transformers to 4.57, which
refuses torch.load of .bin files on torch < 2.6 (CVE-2025-32434).
The converted model.safetensors files are generated locally and are
intentionally not committed (~840MB).

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>

scripts/convert_tts_weights_to_safetensors.py

@@ -0,0 +1,47 @@
+"""将 TTS 预训练权重 (.bin) 转换为 safetensors。
+
+qwen-asr 分支将 transformers 升级到 4.57+，其安全策略 (CVE-2025-32434)
+拒绝在 torch < 2.6 上加载 pytorch_model.bin。transformers 加载时优先使用
+model.safetensors，因此本地转换一次即可，无需升级 torch。
+
+用法: python scripts/convert_tts_weights_to_safetensors.py
+"""
+from pathlib import Path
+
+import torch
+from safetensors.torch import save_file
+
+MOYOYO_PRETRAINED_PATH = Path(__file__).parent.parent / "assets" / "models" / "tts" / "moyoyo"
+
+PRETRAINED_DIRS = [
+    "chinese-roberta-wwm-ext-large",
+    "chinese-hubert-base",
+]
+
+
+def main():
+    for dirname in PRETRAINED_DIRS:
+        model_dir = MOYOYO_PRETRAINED_PATH / dirname
+        bin_path = model_dir / "pytorch_model.bin"
+        st_path = model_dir / "model.safetensors"
+
+        if st_path.exists():
+            print(f"已存在，跳过: {st_path}")
+            continue
+        if not bin_path.exists():
+            print(f"找不到权重文件: {bin_path}")
+            continue
+
+        state_dict = torch.load(bin_path, map_location="cpu", weights_only=True)
+        # clone 断开共享内存，safetensors 不允许张量间共享存储
+        state_dict = {
+            key: value.clone().contiguous()
+            for key, value in state_dict.items()
+            if isinstance(value, torch.Tensor)
+        }
+        save_file(state_dict, st_path, metadata={"format": "pt"})
+        print(f"{dirname}: {len(state_dict)} tensors -> {st_path.stat().st_size // 1024 ** 2} MB")
+
+
+if __name__ == "__main__":
+    main()