Export https://huggingface.co/nvidia/parakeet-tdt-0.6b-v3 to sherpa-onnx (#2500)

This PR adds support for the newer version (v3) of NVIDIA's parakeet-tdt-0.6b model by exporting it to sherpa-onnx format. The v3 model supports 25 languages, maintaining the same usage pattern as v2 but with improved language coverage.

-name: export-nemo-parakeet-tdt-0.6b-v2
+name: export-nemo-parakeet-tdt-0.6b
 
 on:
   push:
@@ -10,81 +10,111 @@ concurrency:
   group: export-nemo-parakeet-tdt-0.6b-v2-${{ github.ref }}
   cancel-in-progress: true
 
+env:
+  HF_HUB_ENABLE_HF_TRANSFER: "0"
+
 jobs:
-  export-nemo-parakeet-tdt-0_6b-v2:
+  export-nemo-parakeet-tdt-0_6b:
     if: github.repository_owner == 'k2-fsa' || github.repository_owner == 'csukuangfj'
-    name: parakeet tdt 0.6b v2
+    name: parakeet tdt 0.6b ${{ matrix.version }}
     runs-on: ${{ matrix.os }}
     strategy:
       fail-fast: false
       matrix:
         os: [macos-latest]
         python-version: ["3.10"]
+        version: ["v2", "v3"]
 
     steps:
       - uses: actions/checkout@v4
 
+      - name: Show disk space
+        run: |
+          df -h
+
+      # See https://github.com/vlayer-xyz/vlayer/pull/543/files
+      # Free up disk space as the macOS runners end up using most for Xcode
+      # versions we don't need and use iOS simulators.
+      - name: Free up disk space
+        run: |
+          echo '*** Delete iOS simulators and their caches'
+          xcrun simctl delete all
+          sudo rm -rf ~/Library/Developer/CoreSimulator/Caches/*
+
+      - name: Show disk space
+        run: |
+          df -h
+
       - name: Setup Python ${{ matrix.python-version }}
         uses: actions/setup-python@v5
         with:
           python-version: ${{ matrix.python-version }}
 
-      - name: Run
+      - name: Run ${{ matrix.version }}
+        if: matrix.version == 'v2'
         shell: bash
         run: |
           cd scripts/nemo/parakeet-tdt-0.6b-v2
           ./run.sh
 
           ls -lh *.onnx
+          ls -lh *.weights
+
           mv -v *.onnx ../../..
+          mv -v *.weights ../../..
           mv -v tokens.txt ../../..
           mv 2086-149220-0033.wav ../../../0.wav
 
-      - name: Collect files (fp32)
+      - name: Run ${{ matrix.version }}
+        if: matrix.version == 'v3'
         shell: bash
         run: |
-          d=sherpa-onnx-nemo-parakeet-tdt-0.6b-v2
-          mkdir -p $d
-          cp encoder.int8.onnx $d
-          cp decoder.onnx $d
-          cp joiner.onnx $d
-          cp tokens.txt $d
-
-          mkdir $d/test_wavs
-          cp 0.wav $d/test_wavs
+          cd scripts/nemo/parakeet-tdt-0.6b-v3
+          ./run.sh
 
-          tar cjfv $d.tar.bz2 $d
+          ls -lh *.onnx
+          mv -v *.onnx ../../..
+          mv -v *.weights ../../..
+          mv -v tokens.txt ../../..
+          mv *.wav ../../../
 
-      - name: Collect files (int8)
+      - name: Collect files (fp32)
         shell: bash
         run: |
-          d=sherpa-onnx-nemo-parakeet-tdt-0.6b-v2-int8
+          version=${{ matrix.version }}
+          d=sherpa-onnx-nemo-parakeet-tdt-0.6b-$version
           mkdir -p $d
-          cp encoder.int8.onnx $d
-          cp decoder.int8.onnx $d
-          cp joiner.int8.onnx $d
-          cp tokens.txt $d
+          cp -v encoder.onnx $d
+          cp -v encoder.weights $d
+          cp -v decoder.onnx $d
+          cp -v joiner.onnx $d
+          cp -v tokens.txt $d
 
           mkdir $d/test_wavs
-          cp 0.wav $d/test_wavs
+          cp -v *.wav $d/test_wavs
 
-          tar cjfv $d.tar.bz2 $d
+          # tar cjfv $d.tar.bz2 $d
+
+          # ls -lh *.tar.bz2
 
-      - name: Collect files (fp16)
+      - name: Collect files (int8)
         shell: bash
         run: |
-          d=sherpa-onnx-nemo-parakeet-tdt-0.6b-v2-fp16
+          version=${{ matrix.version }}
+          d=sherpa-onnx-nemo-parakeet-tdt-0.6b-$version-int8
           mkdir -p $d
-          cp encoder.fp16.onnx $d
-          cp decoder.fp16.onnx $d
-          cp joiner.fp16.onnx $d
-          cp tokens.txt $d
+          cp -v encoder.int8.onnx $d
+          cp -v decoder.int8.onnx $d
+          cp -v joiner.int8.onnx $d
+          cp -v tokens.txt $d
 
           mkdir $d/test_wavs
-          cp 0.wav $d/test_wavs
+          cp -v *.wav $d/test_wavs
 
           tar cjfv $d.tar.bz2 $d
 
+          ls -lh *.tar.bz2
+
       - name: Publish to huggingface
         env:
           HF_TOKEN: ${{ secrets.HF_TOKEN }}
@@ -94,13 +124,13 @@ jobs:
           timeout_seconds: 200
           shell: bash
           command: |
+            version=${{ matrix.version }}
             git config --global user.email "csukuangfj@gmail.com"
             git config --global user.name "Fangjun Kuang"
 
             models=(
-              sherpa-onnx-nemo-parakeet-tdt-0.6b-v2
-              sherpa-onnx-nemo-parakeet-tdt-0.6b-v2-int8
-              sherpa-onnx-nemo-parakeet-tdt-0.6b-v2-fp16
+              sherpa-onnx-nemo-parakeet-tdt-0.6b-$version
+              sherpa-onnx-nemo-parakeet-tdt-0.6b-$version-int8
             )
 
             for m in ${models[@]}; do
@@ -112,6 +142,7 @@ jobs:
               cd huggingface
               git lfs track "*.onnx"
               git lfs track "*.wav"
+              git lfs track "*.weights"
               git status
               git add .
               git status

@@ -681,6 +681,22 @@ def get_models():
             popd
             """,
         ),
+        Model(
+            model_name="sherpa-onnx-nemo-parakeet-tdt-0.6b-v3-int8",
+            idx=40,
+            lang="multi",
+            lang2="25_languages",
+            short_name="parakeet_tdt_0.6b_v3",
+            cmd="""
+            pushd $model_name
+
+            rm -rfv test_wavs
+
+            ls -lh
+
+            popd
+            """,
+        ),
     ]
     return models
 

 #!/usr/bin/env python3
 # Copyright      2025  Xiaomi Corp.        (authors: Fangjun Kuang)
 
+import os
 from pathlib import Path
 from typing import Dict
-import os
 
 import nemo.collections.asr as nemo_asr
 import onnx
-import onnxmltools
 import torch
-from onnxmltools.utils.float16_converter import (
-    convert_float_to_float16,
-    convert_float_to_float16_model_path,
-)
 from onnxruntime.quantization import QuantType, quantize_dynamic
 
 
-def export_onnx_fp16(onnx_fp32_path, onnx_fp16_path):
-    onnx_fp32_model = onnxmltools.utils.load_model(onnx_fp32_path)
-    onnx_fp16_model = convert_float_to_float16(onnx_fp32_model, keep_io_types=True)
-    onnxmltools.utils.save_model(onnx_fp16_model, onnx_fp16_path)
-
-
-def export_onnx_fp16_large_2gb(onnx_fp32_path, onnx_fp16_path):
-    onnx_fp16_model = convert_float_to_float16_model_path(
-        onnx_fp32_path, keep_io_types=True
-    )
-    onnxmltools.utils.save_model(onnx_fp16_model, onnx_fp16_path)
-
-
 def add_meta_data(filename: str, meta_data: Dict[str, str]):
     """Add meta data to an ONNX model. It is changed in-place.
 
@@ -47,11 +29,26 @@ def add_meta_data(filename: str, meta_data: Dict[str, str]):
         meta.key = key
         meta.value = str(value)
 
+    if filename == "encoder.onnx":
+        external_filename = "encoder"
+        onnx.save(
+            model,
+            filename,
+            save_as_external_data=True,
+            all_tensors_to_one_file=True,
+            location=external_filename + ".weights",
+        )
+    else:
         onnx.save(model, filename)
 
 
 @torch.no_grad()
 def main():
+    if Path("./parakeet-tdt-0.6b-v2.nemo").is_file():
+        asr_model = nemo_asr.models.ASRModel.restore_from(
+            restore_path="./parakeet-tdt-0.6b-v2.nemo"
+        )
+    else:
         asr_model = nemo_asr.models.ASRModel.from_pretrained(
             model_name="nvidia/parakeet-tdt-0.6b-v2"
         )
@@ -95,13 +92,8 @@ def main():
         )
         os.system("ls -lh *.onnx")
 
-        if m == "encoder":
-            export_onnx_fp16_large_2gb(f"{m}.onnx", f"{m}.fp16.onnx")
-        else:
-            export_onnx_fp16(f"{m}.onnx", f"{m}.fp16.onnx")
-
     add_meta_data("encoder.int8.onnx", meta_data)
-    add_meta_data("encoder.fp16.onnx", meta_data)
+    add_meta_data("encoder.onnx", meta_data)
     print("meta_data", meta_data)
 
 

@@ -9,8 +9,9 @@ log() {
   echo -e "$(date '+%Y-%m-%d %H:%M:%S') (${fname}:${BASH_LINENO[0]}:${FUNCNAME[1]}) $*"
 }
 
-curl -SL -O https://dldata-public.s3.us-east-2.amazonaws.com/2086-149220-0033.wav
+curl -SL -O https://huggingface.co/nvidia/parakeet-tdt-0.6b-v2/resolve/main/parakeet-tdt-0.6b-v2.nemo
 
+curl -SL -O https://dldata-public.s3.us-east-2.amazonaws.com/2086-149220-0033.wav
 
 
 pip install \
@@ -20,7 +21,6 @@ pip install \
   kaldi-native-fbank \
   librosa \
   onnx==1.17.0 \
-  onnxmltools \
   onnxruntime==1.17.1 \
   soundfile
 
@@ -42,11 +42,3 @@ python3 ./test_onnx.py \
   --joiner ./joiner.int8.onnx \
   --tokens ./tokens.txt \
   --wav 2086-149220-0033.wav
-
-echo "---fp16----"
-python3 ./test_onnx.py \
-  --encoder ./encoder.fp16.onnx \
-  --decoder ./decoder.fp16.onnx \
-  --joiner ./joiner.fp16.onnx \
-  --tokens ./tokens.txt \
-  --wav 2086-149220-0033.wav

+#!/usr/bin/env python3
+# Copyright      2025  Xiaomi Corp.        (authors: Fangjun Kuang)
+
+from pathlib import Path
+from typing import Dict
+import os
+
+import nemo.collections.asr as nemo_asr
+import onnx
+import torch
+from onnxruntime.quantization import QuantType, quantize_dynamic
+
+
+def add_meta_data(filename: str, meta_data: Dict[str, str]):
+    """Add meta data to an ONNX model. It is changed in-place.
+
+    Args:
+      filename:
+        Filename of the ONNX model to be changed.
+      meta_data:
+        Key-value pairs.
+    """
+    model = onnx.load(filename)
+    while len(model.metadata_props):
+        model.metadata_props.pop()
+
+    for key, value in meta_data.items():
+        meta = model.metadata_props.add()
+        meta.key = key
+        meta.value = str(value)
+
+    if filename == "encoder.onnx":
+        external_filename = "encoder"
+        onnx.save(
+            model,
+            filename,
+            save_as_external_data=True,
+            all_tensors_to_one_file=True,
+            location=external_filename + ".weights",
+        )
+    else:
+        onnx.save(model, filename)
+
+
+@torch.no_grad()
+def main():
+    if Path("./parakeet-tdt-0.6b-v3.nemo").is_file():
+        asr_model = nemo_asr.models.ASRModel.restore_from(
+            restore_path="./parakeet-tdt-0.6b-v3.nemo"
+        )
+    else:
+        asr_model = nemo_asr.models.ASRModel.from_pretrained(
+            model_name="nvidia/parakeet-tdt-0.6b-v3"
+        )
+
+    asr_model.eval()
+
+    with open("./tokens.txt", "w", encoding="utf-8") as f:
+        for i, s in enumerate(asr_model.joint.vocabulary):
+            f.write(f"{s} {i}\n")
+        f.write(f"<blk> {i+1}\n")
+        print("Saved to tokens.txt")
+
+    asr_model.encoder.export("encoder.onnx")
+    asr_model.decoder.export("decoder.onnx")
+    asr_model.joint.export("joiner.onnx")
+    os.system("ls -lh *.onnx")
+
+    normalize_type = asr_model.cfg.preprocessor.normalize
+    if normalize_type == "NA":
+        normalize_type = ""
+
+    meta_data = {
+        "vocab_size": asr_model.decoder.vocab_size,
+        "normalize_type": normalize_type,
+        "pred_rnn_layers": asr_model.decoder.pred_rnn_layers,
+        "pred_hidden": asr_model.decoder.pred_hidden,
+        "subsampling_factor": 8,
+        "model_type": "EncDecRNNTBPEModel",
+        "version": "2",
+        "model_author": "NeMo",
+        "url": "https://huggingface.co/nvidia/parakeet-tdt-0.6b-v3",
+        "comment": "Only the transducer branch is exported",
+        "feat_dim": 128,
+    }
+
+    for m in ["encoder", "decoder", "joiner"]:
+        quantize_dynamic(
+            model_input=f"./{m}.onnx",
+            model_output=f"./{m}.int8.onnx",
+            weight_type=QuantType.QUInt8 if m == "encoder" else QuantType.QInt8,
+        )
+        os.system("ls -lh *.onnx")
+
+    add_meta_data("encoder.int8.onnx", meta_data)
+    add_meta_data("encoder.onnx", meta_data)
+    print("meta_data", meta_data)
+
+
+if __name__ == "__main__":
+    main()

+#!/usr/bin/env bash
+# Copyright      2025  Xiaomi Corp.        (authors: Fangjun Kuang)
+
+set -ex
+
+log() {
+  # This function is from espnet
+  local fname=${BASH_SOURCE[1]##*/}
+  echo -e "$(date '+%Y-%m-%d %H:%M:%S') (${fname}:${BASH_LINENO[0]}:${FUNCNAME[1]}) $*"
+}
+
+curl -SL -O https://huggingface.co/nvidia/parakeet-tdt-0.6b-v3/resolve/main/parakeet-tdt-0.6b-v3.nemo
+
+curl -SL -O https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/en.wav
+curl -SL -O https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/de.wav
+curl -SL -O https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/fr.wav
+curl -SL -O https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/es.wav
+
+ls -lh
+
+
+pip install \
+  nemo_toolkit['asr'] \
+  "numpy<2" \
+  ipython \
+  kaldi-native-fbank \
+  librosa \
+  onnx==1.17.0 \
+  onnxruntime==1.17.1 \
+  soundfile
+
+python3 ./export_onnx.py
+ls -lh *.onnx
+
+for w in en.wav de.wav fr.wav es.wav; do
+  echo "---fp32----"
+  python3 ./test_onnx.py \
+    --encoder ./encoder.int8.onnx \
+    --decoder ./decoder.onnx \
+    --joiner ./joiner.onnx \
+    --tokens ./tokens.txt \
+    --wav $w
+
+  echo "---int8----"
+  python3 ./test_onnx.py \
+    --encoder ./encoder.int8.onnx \
+    --decoder ./decoder.int8.onnx \
+    --joiner ./joiner.int8.onnx \
+    --tokens ./tokens.txt \
+    --wav $w
+done

+../parakeet-tdt-0.6b-v2/test_onnx.py
\ No newline at end of file

@@ -46,7 +46,7 @@ bool OfflineTtsModelConfig::Validate() const {
     return kitten.Validate();
   }
 
-  SHERPA_ONNX_LOGE("Please provide at exactly one tts model.");
+  SHERPA_ONNX_LOGE("Please provide exactly one tts model.");
 
   return false;
 }

@@ -65,7 +65,7 @@ struct GeneratedAudio {
 
 class OfflineTtsImpl;
 
-// If the callback returns 0, then it stop generating
+// If the callback returns 0, then it stops generating
 // if the callback returns 1, then it keeps generating
 using GeneratedAudioCallback = std::function<int32_t(
     const float * /*samples*/, int32_t /*n*/, float /*progress*/)>;

@@ -677,6 +677,19 @@ fun getOfflineModelConfig(type: Int): OfflineModelConfig? {
                 tokens = "$modelDir/tokens.txt",
             )
         }
+
+        40 -> {
+            val modelDir = "sherpa-onnx-nemo-parakeet-tdt-0.6b-v3-int8"
+            return OfflineModelConfig(
+                transducer = OfflineTransducerModelConfig(
+                    encoder = "$modelDir/encoder.int8.onnx",
+                    decoder = "$modelDir/decoder.int8.onnx",
+                    joiner = "$modelDir/joiner.int8.onnx",
+                ),
+                tokens = "$modelDir/tokens.txt",
+                modelType = "nemo_transducer",
+            )
+        }
     }
     return null
 }