add nemo models

model.py

@@ -987,6 +987,82 @@ def _get_french_pre_trained_model(
     return recognizer
 
 
+@lru_cache(maxsize=10)
+def _get_sherpa_onnx_nemo_transducer_models(
+    repo_id: str,
+    decoding_method: str,
+    num_active_paths: int,
+) -> sherpa_onnx.OnlineRecognizer:
+    assert repo_id in [
+        "csukuangfj/sherpa-onnx-nemo-parakeet_tdt_transducer_110m-en-36000",
+    ], repo_id
+
+    encoder_model = _get_nn_model_filename(
+        repo_id=repo_id,
+        filename="encoder.onnx",
+        subfolder=".",
+    )
+
+    decoder_model = _get_nn_model_filename(
+        repo_id=repo_id,
+        filename="decoder.onnx",
+        subfolder=".",
+    )
+
+    joiner_model = _get_nn_model_filename(
+        repo_id=repo_id,
+        filename="joiner.onnx",
+        subfolder=".",
+    )
+
+    tokens = _get_token_filename(repo_id=repo_id, subfolder=".")
+
+    recognizer = sherpa_onnx.OnlineRecognizer.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,
+        max_active_paths=num_active_paths,
+    )
+
+    return recognizer
+
+
+@lru_cache(maxsize=10)
+def _get_sherpa_onnx_nemo_ctc_models(
+    repo_id: str,
+    decoding_method: str,
+    num_active_paths: int,
+) -> sherpa_onnx.OfflineRecognizer:
+    assert repo_id in [
+        "csukuangfj/sherpa-onnx-nemo-parakeet_tdt_ctc_110m-en-36000",
+    ], repo_id
+
+    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_nemo_ctc(
+        tokens=tokens,
+        model=model,
+        num_threads=2,
+        sample_rate=16000,
+        feature_dim=80,
+        decoding_method=decoding_method,
+        max_active_paths=num_active_paths,
+    )
+
+    return recognizer
+
+
 @lru_cache(maxsize=10)
 def _get_sherpa_onnx_offline_zipformer_pre_trained_model(
     repo_id: str,
@@ -1505,6 +1581,8 @@ english_models = {
     "whisper-tiny.en": _get_whisper_model,
     "whisper-base.en": _get_whisper_model,
     "whisper-small.en": _get_whisper_model,
+    "csukuangfj/sherpa-onnx-nemo-parakeet_tdt_ctc_110m-en-36000": _get_sherpa_onnx_nemo_ctc_models,
+    "csukuangfj/sherpa-onnx-nemo-parakeet_tdt_transducer_110m-en-36000": _get_sherpa_onnx_nemo_transducer_models,
     #  "whisper-medium.en": _get_whisper_model,
     "csukuangfj/sherpa-onnx-zipformer-en-libriheavy-20230926-large": _get_sherpa_onnx_offline_zipformer_pre_trained_model,
     "csukuangfj/sherpa-onnx-zipformer-en-libriheavy-20230926-medium": _get_sherpa_onnx_offline_zipformer_pre_trained_model,