add a new model

model.py

@@ -178,6 +178,10 @@ def get_pretrained_model(
         return more_than_1600_languages_models[repo_id](
             repo_id, decoding_method=decoding_method, num_active_paths=num_active_paths
         )
+    elif repo_id in funsar_nano_31_languages_models:
+        return funsar_nano_31_languages_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
@@ -2031,15 +2035,24 @@ def _get_sense_voice_pre_trained_model(
     num_active_paths: int,
 ) -> sherpa_onnx.OfflineRecognizer:
     assert repo_id in [
+        "csukuangfj/sherpa-onnx-sense-voice-funasr-nano-int8-2025-12-17",
+        "csukuangfj/sherpa-onnx-sense-voice-funasr-nano-2025-12-17",
         "csukuangfj/sherpa-onnx-sense-voice-zh-en-ja-ko-yue-2024-07-17",
         "csukuangfj/sherpa-onnx-sense-voice-zh-en-ja-ko-yue-int8-2025-09-09",
     ], repo_id
 
-    nn_model = _get_nn_model_filename(
-        repo_id=repo_id,
-        filename="model.int8.onnx",
-        subfolder=".",
-    )
+    if repo_id == "csukuangfj/sherpa-onnx-sense-voice-funasr-nano-2025-12-17":
+        nn_model = _get_nn_model_filename(
+            repo_id=repo_id,
+            filename="model.onnx",
+            subfolder=".",
+        )
+    else:
+        nn_model = _get_nn_model_filename(
+            repo_id=repo_id,
+            filename="model.int8.onnx",
+            subfolder=".",
+        )
 
     tokens = _get_token_filename(repo_id=repo_id, subfolder=".")
 
@@ -2275,6 +2288,11 @@ english_models = {
     "csukuangfj/wenet-english-model": _get_wenet_model,
 }
 
+funsar_nano_31_languages_models = {
+    "csukuangfj/sherpa-onnx-sense-voice-funasr-nano-int8-2025-12-17": _get_sense_voice_pre_trained_model,
+    "csukuangfj/sherpa-onnx-sense-voice-funasr-nano-2025-12-17": _get_sense_voice_pre_trained_model,
+}
+
 more_than_1600_languages_models = {
     "csukuangfj/sherpa-onnx-omnilingual-asr-1600-languages-300M-ctc-int8-2025-11-12": _get_sherpa_onnx_omnilingual_asr_models,
     "csukuangfj/sherpa-onnx-omnilingual-asr-1600-languages-300M-ctc-2025-11-12": _get_sherpa_onnx_omnilingual_asr_models,
@@ -2394,6 +2412,7 @@ portuguese_brazlian_models = {
 
 
 all_models = {
+    **funsar_nano_31_languages_models,
     **more_than_1600_languages_models,
     **twenty_five_languages_models,
     **multi_lingual_models,
@@ -2418,6 +2437,7 @@ all_models = {
 }
 
 language_to_models = {
+    "31 languages (FunASR Nano)": list(funsar_nano_31_languages_models.keys()),
     "1600+ languages": list(more_than_1600_languages_models.keys()),
     "25 European languages": list(twenty_five_languages_models.keys()),
     "Multi-lingual (east aisa)": list(multi_lingual_models.keys()),

requirements.txt

@@ -10,7 +10,7 @@ numpy<2
 
 huggingface_hub
 
-https://huggingface.co/csukuangfj/sherpa-onnx-wheels/resolve/main/cpu/1.12.17/sherpa_onnx_core-1.12.17-py3-none-manylinux2014_x86_64.whl
-https://huggingface.co/csukuangfj/sherpa-onnx-wheels/resolve/main/cpu/1.12.17/sherpa_onnx-1.12.17-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.whl
+https://huggingface.co/csukuangfj/sherpa-onnx-wheels/resolve/main/cpu/1.12.19/sherpa_onnx_core-1.12.19-py3-none-manylinux2014_x86_64.whl
+https://huggingface.co/csukuangfj/sherpa-onnx-wheels/resolve/main/cpu/1.12.19/sherpa_onnx-1.12.19-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.whl
 
 #sherpa-onnx>=1.12.6