add a new model

model.py

@@ -1627,6 +1627,41 @@ def _get_streaming_zipformer_ctc_pre_trained_model(
     return recognizer
 
 
+@lru_cache(maxsize=10)
+def _get_non_streaming_wenet_ctc_pre_trained_model(
+    repo_id: str,
+    decoding_method: str,
+    num_active_paths: int,
+) -> sherpa_onnx.OfflineRecognizer:
+    assert repo_id in [
+        "csukuangfj/sherpa-onnx-wenetspeech-yue-u2pp-conformer-ctc-zh-en-cantonese-int8-2025-09-10"
+    ], repo_id
+
+    if "int8" in repo_id:
+        model = _get_nn_model_filename(
+            repo_id=repo_id,
+            filename="model.int8.onnx",
+            subfolder=".",
+        )
+    else:
+        model = _get_nn_model_filename(
+            repo_id=repo_id,
+            filename="model.onnx",
+            subfolder=".",
+        )
+    tokens = _get_token_filename(repo_id=repo_id, subfolder=".")
+
+    recognizer = sherpa_onnx.OfflineRecognizer.from_wenet_ctc(
+        tokens=tokens,
+        model=model,
+        num_threads=2,
+        sample_rate=16000,
+        feature_dim=80,
+    )
+
+    return recognizer
+
+
 @lru_cache(maxsize=10)
 def _get_non_streaming_zipformer_ctc_pre_trained_model(
     repo_id: str,
@@ -2254,6 +2289,7 @@ chinese_cantonese_english_japanese_korean_models = {
 }
 
 cantonese_models = {
+    "csukuangfj/sherpa-onnx-wenetspeech-yue-u2pp-conformer-ctc-zh-en-cantonese-int8-2025-09-10": _get_non_streaming_wenet_ctc_pre_trained_model,
     "zrjin/icefall-asr-mdcc-zipformer-2024-03-11": _get_zrjin_cantonese_pre_trained_model,
 }