Update model.py

model.py

@@ -362,72 +362,72 @@ def _get_offline_pre_trained_model(
     return recognizer
 
 
-@lru_cache(maxsize=10)
-def _get_vietnamese_pretrained_model(
-    repo_id: str, decoding_method: str, num_active_paths: int
-) -> sherpa_onnx.OfflineRecognizer:
-    assert repo_id in (
-        "csukuangfj/sherpa-onnx-zipformer-vi-int8-2025-04-20",
-        "csukuangfj/sherpa-onnx-zipformer-vi-2025-04-20",
-    ), repo_id
-
-    # decoder_model = _get_nn_model_filename(
-    #     repo_id=repo_id,
-    #     filename="decoder-epoch-12-avg-8.onnx",
-    #     subfolder=".",
-    # )
-
-    decoder_model = "decoder-epoch-45-avg-25.onnx"
-
-    if repo_id == "csukuangfj/sherpa-onnx-zipformer-vi-int8-2025-04-20":
-        # encoder_model = _get_nn_model_filename(
-        #     repo_id=repo_id,
-        #     filename="encoder-epoch-12-avg-8.int8.onnx",
-        #     subfolder=".",
-        # )
-
-        encoder_model = "encoder-epoch-45-avg-25.int8.onnx"
-
-        # joiner_model = _get_nn_model_filename(
-        #     repo_id=repo_id,
-        #     filename="joiner-epoch-12-avg-8.int8.onnx",
-        #     subfolder=".",
-        # )
-        joiner_model = "joiner-epoch-45-avg-25.int8.onnx"
-    elif repo_id == "csukuangfj/sherpa-onnx-zipformer-vi-2025-04-20":
-        # encoder_model = _get_nn_model_filename(
-        #     repo_id=repo_id,
-        #     filename="encoder-epoch-12-avg-8.onnx",
-        #     subfolder=".",
-        # )
-
-        encoder_model = "encoder-epoch-45-avg-25.onnx"
-
-        # joiner_model = _get_nn_model_filename(
-        #     repo_id=repo_id,
-        #     filename="joiner-epoch-12-avg-8.onnx",
-        #     subfolder=".",
-        # )
-        joiner_model = "joiner-epoch-45-avg-25.onnx"
-    else:
-        raise ValueError(f"repo_id: {repo_id}")
-
-    # tokens = _get_token_filename(repo_id=repo_id, subfolder=".")
-
-    tokens = "tokens.txt"
-
-    recognizer = sherpa_onnx.OfflineRecognizer.from_transducer(
-        tokens=tokens,
-        encoder=encoder_model,
-        decoder=decoder_model,
-        joiner=joiner_model,
-        num_threads=2,
-        sample_rate=16000,
-        feature_dim=80,
-        decoding_method=decoding_method,
-    )
-
-    return recognizer
+# @lru_cache(maxsize=10)
+# def _get_vietnamese_pretrained_model(
+#     repo_id: str, decoding_method: str, num_active_paths: int
+# ) -> sherpa_onnx.OfflineRecognizer:
+#     assert repo_id in (
+#         "csukuangfj/sherpa-onnx-zipformer-vi-int8-2025-04-20",
+#         "csukuangfj/sherpa-onnx-zipformer-vi-2025-04-20",
+#     ), repo_id
+
+#     # decoder_model = _get_nn_model_filename(
+#     #     repo_id=repo_id,
+#     #     filename="decoder-epoch-12-avg-8.onnx",
+#     #     subfolder=".",
+#     # )
+
+#     decoder_model = "decoder-epoch-45-avg-25.onnx"
+
+#     if repo_id == "csukuangfj/sherpa-onnx-zipformer-vi-int8-2025-04-20":
+#         # encoder_model = _get_nn_model_filename(
+#         #     repo_id=repo_id,
+#         #     filename="encoder-epoch-12-avg-8.int8.onnx",
+#         #     subfolder=".",
+#         # )
+
+#         encoder_model = "encoder-epoch-45-avg-25.int8.onnx"
+
+#         # joiner_model = _get_nn_model_filename(
+#         #     repo_id=repo_id,
+#         #     filename="joiner-epoch-12-avg-8.int8.onnx",
+#         #     subfolder=".",
+#         # )
+#         joiner_model = "joiner-epoch-45-avg-25.int8.onnx"
+#     elif repo_id == "csukuangfj/sherpa-onnx-zipformer-vi-2025-04-20":
+#         # encoder_model = _get_nn_model_filename(
+#         #     repo_id=repo_id,
+#         #     filename="encoder-epoch-12-avg-8.onnx",
+#         #     subfolder=".",
+#         # )
+
+#         encoder_model = "encoder-epoch-45-avg-25.onnx"
+
+#         # joiner_model = _get_nn_model_filename(
+#         #     repo_id=repo_id,
+#         #     filename="joiner-epoch-12-avg-8.onnx",
+#         #     subfolder=".",
+#         # )
+#         joiner_model = "joiner-epoch-45-avg-25.onnx"
+#     else:
+#         raise ValueError(f"repo_id: {repo_id}")
+
+#     # tokens = _get_token_filename(repo_id=repo_id, subfolder=".")
+
+#     tokens = "tokens.txt"
+
+#     recognizer = sherpa_onnx.OfflineRecognizer.from_transducer(
+#         tokens=tokens,
+#         encoder=encoder_model,
+#         decoder=decoder_model,
+#         joiner=joiner_model,
+#         num_threads=2,
+#         sample_rate=16000,
+#         feature_dim=80,
+#         decoding_method=decoding_method,
+#     )
+
+#     return recognizer
 
 
 @lru_cache(maxsize=10)
@@ -695,7 +695,7 @@ def _get_whisper_model(
 
 
 @lru_cache(maxsize=10)
-def _get_gigaspeech_pre_trained_model(
+def _get_vietnamese_pretrained_model(
     repo_id: str,
     decoding_method: str,
     num_active_paths: int,
@@ -703,6 +703,10 @@ def _get_gigaspeech_pre_trained_model(
     # assert repo_id in [
     #     "wgb14/icefall-asr-gigaspeech-pruned-transducer-stateless2",
     # ], repo_id
+    assert repo_id in (
+        "csukuangfj/sherpa-onnx-zipformer-vi-int8-2025-04-20",
+        "csukuangfj/sherpa-onnx-zipformer-vi-2025-04-20",
+    ), repo_id
 
     nn_model = "jit_script.pt"
     tokens = "tokens.txt"