add more models

model.py

@@ -170,6 +170,10 @@ def get_pretrained_model(
         return multi_lingual_models[repo_id](
             repo_id, decoding_method=decoding_method, num_active_paths=num_active_paths
         )
+    elif repo_id in twenty_five_languages_models:
+        return twenty_five_languages_models[repo_id](
+            repo_id, decoding_method=decoding_method, num_active_paths=num_active_paths
+        )
     elif repo_id in chinese_models:
         return chinese_models[repo_id](
             repo_id, decoding_method=decoding_method, num_active_paths=num_active_paths
@@ -1594,12 +1598,14 @@ def _get_streaming_zipformer_pre_trained_model(
         "csukuangfj/sherpa-onnx-streaming-zipformer-en-kroko-2025-08-06",
         "csukuangfj/sherpa-onnx-streaming-zipformer-es-kroko-2025-08-06",
         "csukuangfj/sherpa-onnx-streaming-zipformer-fr-kroko-2025-08-06",
+        "csukuangfj/sherpa-onnx-streaming-zipformer-de-kroko-2025-08-06",
     ], repo_id
 
     if repo_id in [
         "csukuangfj/sherpa-onnx-streaming-zipformer-en-kroko-2025-08-06",
         "csukuangfj/sherpa-onnx-streaming-zipformer-es-kroko-2025-08-06",
         "csukuangfj/sherpa-onnx-streaming-zipformer-fr-kroko-2025-08-06",
+        "csukuangfj/sherpa-onnx-streaming-zipformer-de-kroko-2025-08-06",
     ]:
         encoder_model = _get_nn_model_filename(
             repo_id=repo_id,
@@ -2089,6 +2095,10 @@ english_models = {
     "csukuangfj/wenet-english-model": _get_wenet_model,
 }
 
+twenty_five_languages_models = {
+    "csukuangfj/sherpa-onnx-nemo-parakeet-tdt-0.6b-v3-int8": _get_sherpa_onnx_nemo_transducer_models_int8,
+}
+
 multi_lingual_models = {
     "csukuangfj/sherpa-onnx-dolphin-base-ctc-multi-lang-int8-2025-04-02": _get_dolphin_ctc_models,
     "csukuangfj/sherpa-onnx-dolphin-small-ctc-multi-lang-int8-2025-04-02": _get_dolphin_ctc_models,
@@ -2115,6 +2125,8 @@ arabic_models = {
 }
 
 german_models = {
+    "csukuangfj/sherpa-onnx-nemo-parakeet-tdt-0.6b-v3-int8": _get_sherpa_onnx_nemo_transducer_models_int8,
+    "csukuangfj/sherpa-onnx-streaming-zipformer-de-kroko-2025-08-06": _get_streaming_zipformer_pre_trained_model,
     "csukuangfj/sherpa-onnx-nemo-transducer-stt_de_fastconformer_hybrid_large_pc": _get_sherpa_onnx_nemo_transducer_models,
     "csukuangfj/sherpa-onnx-nemo-transducer-stt_de_fastconformer_hybrid_large_pc-int8": _get_sherpa_onnx_nemo_transducer_models_int8,
     "csukuangfj/sherpa-onnx-nemo-stt_de_fastconformer_hybrid_large_pc": _get_sherpa_onnx_nemo_ctc_models,
@@ -2123,11 +2135,13 @@ german_models = {
 }
 
 french_models = {
+    "csukuangfj/sherpa-onnx-nemo-parakeet-tdt-0.6b-v3-int8": _get_sherpa_onnx_nemo_transducer_models_int8,
     "shaojieli/sherpa-onnx-streaming-zipformer-fr-2023-04-14": _get_french_pre_trained_model,
     "csukuangfj/sherpa-onnx-streaming-zipformer-fr-kroko-2025-08-06": _get_streaming_zipformer_pre_trained_model,
 }
 
 spanish_models = {
+    "csukuangfj/sherpa-onnx-nemo-parakeet-tdt-0.6b-v3-int8": _get_sherpa_onnx_nemo_transducer_models_int8,
     "csukuangfj/sherpa-onnx-streaming-zipformer-es-kroko-2025-08-06": _get_streaming_zipformer_pre_trained_model,
 }
 
@@ -2138,6 +2152,7 @@ japanese_models = {
 }
 
 russian_models = {
+    "csukuangfj/sherpa-onnx-nemo-parakeet-tdt-0.6b-v3-int8": _get_sherpa_onnx_nemo_transducer_models_int8,
     "csukuangfj/sherpa-onnx-nemo-transducer-giga-am-v2-russian-2025-04-19": _get_russian_pre_trained_model,
     "csukuangfj/sherpa-onnx-nemo-ctc-giga-am-v2-russian-2025-04-19": _get_russian_pre_trained_model_ctc,
     "csukuangfj/sherpa-onnx-nemo-transducer-giga-am-russian-2024-10-24": _get_russian_pre_trained_model,
@@ -2174,6 +2189,7 @@ vietnamese_models = {
 }
 
 portuguese_brazlian_models = {
+    "csukuangfj/sherpa-onnx-nemo-parakeet-tdt-0.6b-v3-int8": _get_sherpa_onnx_nemo_transducer_models_int8,
     "csukuangfj/sherpa-onnx-nemo-stt_pt_fastconformer_hybrid_large_pc": _get_sherpa_onnx_nemo_ctc_models,
     "csukuangfj/sherpa-onnx-nemo-stt_pt_fastconformer_hybrid_large_pc-int8": _get_sherpa_onnx_nemo_ctc_models,
     "csukuangfj/sherpa-onnx-nemo-transducer-stt_pt_fastconformer_hybrid_large_pc": _get_sherpa_onnx_nemo_transducer_models,
@@ -2182,6 +2198,7 @@ portuguese_brazlian_models = {
 
 
 all_models = {
+    **twenty_five_languages_models,
     **multi_lingual_models,
     **chinese_models,
     **english_models,
@@ -2203,6 +2220,7 @@ all_models = {
 }
 
 language_to_models = {
+    "25 European languages": list(twenty_five_languages_models.keys()),
     "Multi-lingual (east aisa)": list(multi_lingual_models.keys()),
     "超多种中文方言": list(chinese_dialect_models.keys()),
     "Chinese": list(chinese_models.keys()),