add data download instructions

Signed-off-by: tzhouam <tzhouam@connect.ust.hk>

examples/offline_inference/qwen_2_5_omni/README.md

@@ -63,7 +63,16 @@ uv pip install -r requirements.txt
 ```
 
 ## Run examples (Qwen2.5-omni)
-
+Download dataset from seed_tts[https://drive.google.com/file/d/1GlSjVfSHkW3-leKKBlfrjuuTGqQ_xaLP/edit]. To get the prompt, you can:
+```bash
+tar -xf <Your Download Path>/seedtts_testset.tar
+cp seedtts_testset/en/meta.lst examples/offline_inference/qwen_2_5_omni/meta.lst
+python3 examples/offline_inference/qwen_2_5_omni/extract_prompts.py \
+  --input examples/offline_inference/qwen_2_5_omni/meta.lst \
+  --output examples/offline_inference/qwen_2_5_omni/top100.txt \
+  --topk 100 \
+  --pt-output examples/offline_inference/qwen_2_5_omni/top100.pt
+```
 Get into the example folder
 ```bash
 cd examples/offline_inference/qwen_2_5_omni

examples/offline_inference/qwen_2_5_omni/extract_prompts.py

@@ -0,0 +1,48 @@
+#!/usr/bin/env python3
+import argparse
+from typing import Optional
+import os
+import torch
+
+
+def extract_prompt(line: str) -> Optional[str]:
+    # 提取第一个 '|' 与第二个 '|' 之间的内容
+    i = line.find('|')
+    if i == -1:
+        return None
+    j = line.find('|', i + 1)
+    if j == -1:
+        return None
+    return line[i + 1:j].strip()
+
+
+def main() -> None:
+    parser = argparse.ArgumentParser()
+    parser.add_argument("--input", "-i", required=True, help="输入 .lst 文件路径")
+    parser.add_argument("--output", "-o", required=True, help="输出文件路径")
+    parser.add_argument("--topk", "-k", type=int, default=100, help="提取前 K 个 prompt（默认 100）")
+    parser.add_argument("--pt-output", "-p", type=str, default=None, help="可选：输出 .pt 文件路径（默认与 --output 同名 .pt）")
+    args = parser.parse_args()
+
+    prompts = []
+    with open(args.input, "r", encoding="utf-8", errors="ignore") as f:
+        for line in f:
+            if len(prompts) >= args.topk:
+                break
+            p = extract_prompt(line.rstrip("\n"))
+            if p:
+                prompts.append(p)
+
+    with open(args.output, "w", encoding="utf-8") as f:
+        for p in prompts:
+            f.write(p + "\n")
+
+    # 另存为 PyTorch 序列化的 .pt，内容为字符串列表
+    pt_path = args.pt_output if args.pt_output else os.path.splitext(args.output)[0] + ".pt"
+    torch.save(prompts, pt_path)
+
+
+if __name__ == "__main__":
+    main()
+
+