update english + chinese model

model.py

@@ -262,20 +262,28 @@ def _get_wenetspeech_pre_trained_model(
 
 
 @lru_cache(maxsize=10)
-def _get_tal_csasr_pre_trained_model(
+def _get_chinese_english_mixed_model(
     repo_id: str,
     decoding_method: str,
     num_active_paths: int,
 ):
     assert repo_id in [
         "luomingshuang/icefall_asr_tal-csasr_pruned_transducer_stateless5",
+        "ptrnull/icefall-asr-conv-emformer-transducer-stateless2-zh",
     ], repo_id
 
+    if repo_id == "luomingshuang/icefall_asr_tal-csasr_pruned_transducer_stateless5":
+        filename = "cpu_jit.pt"
+        subfolder = "data/lang_char"
+    elif repo_id == "ptrnull/icefall-asr-conv-emformer-transducer-stateless2-zh":
+        filename = "cpu_jit-epoch-11-avg-1.pt"
+        subfolder = "data/lang_char_bpe"
+
     nn_model = _get_nn_model_filename(
         repo_id=repo_id,
-        filename="cpu_jit.pt",
+        filename=filename,
     )
-    tokens = _get_token_filename(repo_id=repo_id)
+    tokens = _get_token_filename(repo_id=repo_id, subfolder=subfolder)
 
     feat_config = sherpa.FeatureConfig()
     feat_config.fbank_opts.frame_opts.samp_freq = sample_rate
@@ -541,7 +549,8 @@ english_models = {
 }
 
 chinese_english_mixed_models = {
-    "luomingshuang/icefall_asr_tal-csasr_pruned_transducer_stateless5": _get_tal_csasr_pre_trained_model,  # noqa
+    "luomingshuang/icefall_asr_tal-csasr_pruned_transducer_stateless5": _get_chinese_english_mixed_model,  # noqa
+    "ptrnull/icefall-asr-conv-emformer-transducer-stateless2-zh": _get_chinese_english_mixed_model,
 }
 
 tibetan_models = {