add updated gigaspeech model

model.py

@@ -880,6 +880,51 @@ def _get_japanese_pre_trained_model(
     return recognizer
 
 
+@lru_cache(maxsize=10)
+def _get_gigaspeech_pre_trained_model_onnx(
+    repo_id: str,
+    decoding_method: str,
+    num_active_paths: int,
+) -> sherpa_onnx.OfflineRecognizer:
+    assert repo_id in [
+        "yfyeung/icefall-asr-gigaspeech-zipformer-2023-10-17",
+    ], repo_id
+
+    encoder_model = _get_nn_model_filename(
+        repo_id=repo_id,
+        filename="encoder-epoch-30-avg-9.onnx",
+        subfolder="exp",
+    )
+
+    decoder_model = _get_nn_model_filename(
+        repo_id=repo_id,
+        filename="decoder-epoch-30-avg-9.onnx",
+        subfolder="exp",
+    )
+
+    joiner_model = _get_nn_model_filename(
+        repo_id=repo_id,
+        filename="joiner-epoch-30-avg-9.onnx",
+        subfolder="exp",
+    )
+
+    tokens = _get_token_filename(repo_id=repo_id, subfolder="data/lang_bpe_500")
+
+    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,
+        max_active_paths=num_active_paths,
+    )
+
+    return recognizer
+
+
 @lru_cache(maxsize=10)
 def _get_paraformer_zh_pre_trained_model(
     repo_id: str,
@@ -971,6 +1016,7 @@ english_models = {
     "whisper-base.en": _get_whisper_model,
     "whisper-small.en": _get_whisper_model,
     #  "whisper-medium.en": _get_whisper_model,
+    "yfyeung/icefall-asr-gigaspeech-zipformer-2023-10-17": _get_gigaspeech_pre_trained_model_onnx,  # noqa
     "wgb14/icefall-asr-gigaspeech-pruned-transducer-stateless2": _get_gigaspeech_pre_trained_model,  # noqa
     "yfyeung/icefall-asr-multidataset-pruned_transducer_stateless7-2023-05-04": _get_english_model,  # noqa
     "yfyeung/icefall-asr-finetune-mux-pruned_transducer_stateless7-2023-05-19": _get_english_model,  # noqa