diff --git a/.github/scripts/docker/Dockerfile b/.github/scripts/docker/Dockerfile
index cf0523401..1b6d0026f 100644
--- a/.github/scripts/docker/Dockerfile
+++ b/.github/scripts/docker/Dockerfile
@@ -55,9 +55,9 @@ RUN pip install --no-cache-dir \
       "numpy<2.0" \
       onnxoptimizer \
       onnxsim \
-      onnx \
+      onnx==1.17.0 \
       onnxmltools \
-      onnxruntime \
+      onnxruntime==1.17.1 \
       piper_phonemize -f https://k2-fsa.github.io/icefall/piper_phonemize.html \
       pypinyin==0.50.0 \
       pytest \
diff --git a/.github/scripts/docker/generate_build_matrix.py b/.github/scripts/docker/generate_build_matrix.py
index 638e19498..7f36e278d 100755
--- a/.github/scripts/docker/generate_build_matrix.py
+++ b/.github/scripts/docker/generate_build_matrix.py
@@ -63,23 +63,24 @@ def get_torchaudio_version(torch_version):
 
 
 def get_matrix(min_torch_version, specified_torch_version, specified_python_version):
-    k2_version = "1.24.4.dev20241029"
-    kaldifeat_version = "1.25.5.dev20241029"
-    version = "20241218"
+    k2_version = "1.24.4.dev20250630"
+    kaldifeat_version = "1.25.5.dev20250630"
+    version = "20250630"
 
     # torchaudio 2.5.0 does not support python 3.13
-    python_version = ["3.8", "3.9", "3.10", "3.11", "3.12"]
+    python_version = ["3.8", "3.9", "3.10", "3.11", "3.12", "3.13"]
     torch_version = []
     torch_version += ["1.13.0", "1.13.1"]
     torch_version += ["2.0.0", "2.0.1"]
-    #  torch_version += ["2.1.0", "2.1.1", "2.1.2"]
-    #  torch_version += ["2.2.0", "2.2.1", "2.2.2"]
+    torch_version += ["2.1.0", "2.1.1", "2.1.2"]
+    torch_version += ["2.2.0", "2.2.1", "2.2.2"]
     # Test only torch >= 2.3.0
     torch_version += ["2.3.0", "2.3.1"]
     torch_version += ["2.4.0"]
     torch_version += ["2.4.1"]
     torch_version += ["2.5.0"]
     torch_version += ["2.5.1"]
+    torch_version += ["2.6.0", "2.7.0", "2.7.1"]
 
     if specified_torch_version:
         torch_version = [specified_torch_version]
@@ -109,12 +110,8 @@ def get_matrix(min_torch_version, specified_torch_version, specified_python_vers
                 # torch>=2.5 requires python 3.10
                 continue
 
-            if t == "2.5.1":
-                k2_version_2 = "1.24.4.dev20241122"
-                kaldifeat_version_2 = "1.25.5.dev20241126"
-            else:
-                k2_version_2 = k2_version
-                kaldifeat_version_2 = kaldifeat_version
+            k2_version_2 = k2_version
+            kaldifeat_version_2 = kaldifeat_version
 
             matrix.append(
                 {
diff --git a/.github/scripts/multi-zh-hans.sh b/.github/scripts/multi-zh-hans.sh
deleted file mode 100755
index e254419ff..000000000
--- a/.github/scripts/multi-zh-hans.sh
+++ /dev/null
@@ -1,200 +0,0 @@
-#!/usr/bin/env bash
-
-set -ex
-
-git config --global user.name "k2-fsa"
-git config --global user.email "csukuangfj@gmail.com"
-git config --global lfs.allowincompletepush true
-
-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]}) $*"
-}
-
-log "pwd: $PWD"
-
-cd egs/multi_zh-hans/ASR
-
-repo_url=https://huggingface.co/zrjin/icefall-asr-multi-zh-hans-zipformer-2023-9-2
-log "Downloading pre-trained model from $repo_url"
-GIT_LFS_SKIP_SMUDGE=1 git clone $repo_url
-repo=$(basename $repo_url)
-pushd $repo
-cd exp
-git lfs pull --include pretrained.pt
-ln -s pretrained.pt epoch-99.pt
-cd ../data/lang_bpe_2000
-ls -lh
-git lfs pull --include L.pt L_disambig.pt Linv.pt bpe.model
-git lfs pull --include "*.model"
-ls -lh
-popd
-
-log "--------------------------------------------"
-log "Export non-streaming ONNX transducer models "
-log "--------------------------------------------"
-./zipformer/export-onnx.py \
-  --tokens $repo/data/lang_bpe_2000/tokens.txt \
-  --use-averaged-model 0 \
-  --epoch 99 \
-  --avg 1 \
-  --exp-dir $repo/exp \
-  --causal False
-
-ls -lh $repo/exp
-
-./zipformer/onnx_pretrained.py \
-  --encoder-model-filename $repo/exp/encoder-epoch-99-avg-1.onnx \
-  --decoder-model-filename $repo/exp/decoder-epoch-99-avg-1.onnx \
-  --joiner-model-filename $repo/exp/joiner-epoch-99-avg-1.onnx \
-  --tokens $repo/data/lang_bpe_2000/tokens.txt \
-  $repo/test_wavs/DEV_T0000000000.wav \
-  $repo/test_wavs/DEV_T0000000001.wav \
-  $repo/test_wavs/DEV_T0000000002.wav \
-  $repo/test_wavs/TEST_MEETING_T0000000113.wav \
-  $repo/test_wavs/TEST_MEETING_T0000000219.wav \
-  $repo/test_wavs/TEST_MEETING_T0000000351.wav
-
-rm -rf $repo
-
-repo_url=https://huggingface.co/zrjin/icefall-asr-multi-zh-hans-zipformer-ctc-streaming-2023-11-05
-log "Downloading pre-trained model from $repo_url"
-GIT_LFS_SKIP_SMUDGE=1 git clone $repo_url
-repo=$(basename $repo_url)
-
-pushd $repo
-cd exp/
-git lfs pull --include pretrained.pt
-rm -fv epoch-20.pt
-rm -fv *.onnx
-ln -s pretrained.pt epoch-20.pt
-cd ../data/lang_bpe_2000
-ls -lh
-git lfs pull --include L.pt L_disambig.pt Linv.pt bpe.model
-git lfs pull --include "*.model"
-ls -lh
-popd
-
-log "----------------------------------------"
-log "Export streaming ONNX CTC models "
-log "----------------------------------------"
-./zipformer/export-onnx-streaming-ctc.py \
-  --exp-dir $repo/exp \
-  --tokens $repo/data/lang_bpe_2000/tokens.txt \
-  --causal 1 \
-  --avg 1 \
-  --epoch 20 \
-  --use-averaged-model 0 \
-  --chunk-size 16 \
-  --left-context-frames 128 \
-  --use-ctc 1
-
-ls -lh $repo/exp/
-
-log "------------------------------------------------------------"
-log "Test exported streaming ONNX CTC models (greedy search)     "
-log "------------------------------------------------------------"
-
-test_wavs=(
-DEV_T0000000000.wav
-DEV_T0000000001.wav
-DEV_T0000000002.wav
-TEST_MEETING_T0000000113.wav
-TEST_MEETING_T0000000219.wav
-TEST_MEETING_T0000000351.wav
-)
-
-for w in ${test_wavs[@]}; do
-  ./zipformer/onnx_pretrained-streaming-ctc.py \
-    --model-filename $repo/exp/ctc-epoch-20-avg-1-chunk-16-left-128.int8.onnx \
-    --tokens $repo/data/lang_bpe_2000/tokens.txt \
-    $repo/test_wavs/$w
-done
-
-log "Upload onnx CTC models to huggingface"
-url=https://huggingface.co/k2-fsa/sherpa-onnx-streaming-zipformer-ctc-multi-zh-hans-2023-12-13
-GIT_LFS_SKIP_SMUDGE=1 git clone $url
-dst=$(basename $url)
-cp -v $repo/exp/ctc*.onnx $dst
-cp -v $repo/data/lang_bpe_2000/tokens.txt $dst
-cp -v $repo/data/lang_bpe_2000/bpe.model $dst
-mkdir -p $dst/test_wavs
-cp -v $repo/test_wavs/*.wav $dst/test_wavs
-cd $dst
-git lfs track "*.onnx" "bpe.model"
-ls -lh
-file bpe.model
-git status
-git add .
-git commit -m "upload model" && git push https://k2-fsa:${HF_TOKEN}@huggingface.co/k2-fsa/$dst main || true
-
-log "Upload models to https://github.com/k2-fsa/sherpa-onnx"
-rm -rf .git
-rm -fv .gitattributes
-cd ..
-tar cjfv $dst.tar.bz2 $dst
-ls -lh *.tar.bz2
-mv -v $dst.tar.bz2 ../../../
-
-log "----------------------------------------"
-log "Export streaming ONNX transducer models "
-log "----------------------------------------"
-
-./zipformer/export-onnx-streaming.py \
-  --exp-dir $repo/exp \
-  --tokens $repo/data/lang_bpe_2000/tokens.txt \
-  --causal 1 \
-  --avg 1 \
-  --epoch 20 \
-  --use-averaged-model 0 \
-  --chunk-size 16 \
-  --left-context-frames 128 \
-  --use-ctc 0
-
-ls -lh $repo/exp
-
-log "------------------------------------------------------------"
-log "Test exported streaming ONNX transducer models (Python code)"
-log "------------------------------------------------------------"
-
-log "test fp32"
-./zipformer/onnx_pretrained-streaming.py \
-  --encoder-model-filename $repo/exp/encoder-epoch-20-avg-1-chunk-16-left-128.onnx \
-  --decoder-model-filename $repo/exp/decoder-epoch-20-avg-1-chunk-16-left-128.onnx \
-  --joiner-model-filename $repo/exp/joiner-epoch-20-avg-1-chunk-16-left-128.onnx \
-  --tokens $repo/data/lang_bpe_2000/tokens.txt \
-  $repo/test_wavs/DEV_T0000000000.wav
-
-log "test int8"
-./zipformer/onnx_pretrained-streaming.py \
-  --encoder-model-filename $repo/exp/encoder-epoch-20-avg-1-chunk-16-left-128.int8.onnx \
-  --decoder-model-filename $repo/exp/decoder-epoch-20-avg-1-chunk-16-left-128.onnx \
-  --joiner-model-filename $repo/exp/joiner-epoch-20-avg-1-chunk-16-left-128.int8.onnx \
-  --tokens $repo/data/lang_bpe_2000/tokens.txt \
-  $repo/test_wavs/DEV_T0000000000.wav
-
-log "Upload onnx transducer models to huggingface"
-
-url=https://huggingface.co/k2-fsa/sherpa-onnx-streaming-zipformer-multi-zh-hans-2023-12-12
-GIT_LFS_SKIP_SMUDGE=1 git clone $url
-dst=$(basename $url)
-cp -v $repo/exp/encoder*.onnx $dst
-cp -v $repo/exp/decoder*.onnx $dst
-cp -v $repo/exp/joiner*.onnx $dst
-cp -v $repo/data/lang_bpe_2000/tokens.txt $dst
-cp -v $repo/data/lang_bpe_2000/bpe.model $dst
-mkdir -p $dst/test_wavs
-cp -v $repo/test_wavs/*.wav $dst/test_wavs
-cd $dst
-git lfs track "*.onnx" bpe.model
-git add .
-git commit -m "upload model" && git push https://k2-fsa:${HF_TOKEN}@huggingface.co/k2-fsa/$dst main || true
-
-log "Upload models to https://github.com/k2-fsa/sherpa-onnx"
-rm -rf .git
-rm -fv .gitattributes
-cd ..
-tar cjfv $dst.tar.bz2 $dst
-ls -lh *.tar.bz2
-mv -v $dst.tar.bz2 ../../../
diff --git a/.github/scripts/multi_zh-hans/ASR/run.sh b/.github/scripts/multi_zh-hans/ASR/run.sh
new file mode 100755
index 000000000..345b64cf0
--- /dev/null
+++ b/.github/scripts/multi_zh-hans/ASR/run.sh
@@ -0,0 +1,756 @@
+#!/usr/bin/env bash
+
+set -ex
+
+git config --global user.name "k2-fsa"
+git config --global user.email "csukuangfj@gmail.com"
+git config --global lfs.allowincompletepush true
+
+python3 -m pip install onnxmltools==1.13.0 onnx==1.17.0 onnxruntime==1.17.1 sherpa-onnx
+
+log() {
+  # This function is from espnet
+  local fname=${BASH_SOURCE[1]##*/}
+  echo -e "$(date '+%Y-%m-%d %H:%M:%S') (${fname}:${BASH_LINENO[0]}:${FUNCNAME[1]}) $*"
+}
+
+cd egs/multi_zh-hans/ASR
+
+log "pwd: $PWD"
+
+function run_2023_9_2() {
+  repo_url=https://huggingface.co/zrjin/icefall-asr-multi-zh-hans-zipformer-2023-9-2
+  log "Downloading pre-trained model from $repo_url"
+  GIT_LFS_SKIP_SMUDGE=1 git clone $repo_url
+  repo=$(basename $repo_url)
+  pushd $repo
+  cd exp
+  git lfs pull --include pretrained.pt
+  ln -s pretrained.pt epoch-99.pt
+  cd ../data/lang_bpe_2000
+  ls -lh
+  git lfs pull --include L.pt L_disambig.pt Linv.pt bpe.model
+  git lfs pull --include "*.model"
+  ls -lh
+  popd
+
+  log "--------------------------------------------"
+  log "Export non-streaming ONNX transducer models "
+  log "--------------------------------------------"
+  ./zipformer/export-onnx.py \
+    --tokens $repo/data/lang_bpe_2000/tokens.txt \
+    --use-averaged-model 0 \
+    --epoch 99 \
+    --avg 1 \
+    --exp-dir $repo/exp \
+    --causal False \
+    --fp16 1
+
+  ls -lh $repo/exp
+
+  ./zipformer/onnx_pretrained.py \
+    --encoder-model-filename $repo/exp/encoder-epoch-99-avg-1.onnx \
+    --decoder-model-filename $repo/exp/decoder-epoch-99-avg-1.onnx \
+    --joiner-model-filename $repo/exp/joiner-epoch-99-avg-1.onnx \
+    --tokens $repo/data/lang_bpe_2000/tokens.txt \
+    $repo/test_wavs/DEV_T0000000000.wav \
+    $repo/test_wavs/DEV_T0000000001.wav \
+    $repo/test_wavs/DEV_T0000000002.wav \
+    $repo/test_wavs/TEST_MEETING_T0000000113.wav \
+    $repo/test_wavs/TEST_MEETING_T0000000219.wav \
+    $repo/test_wavs/TEST_MEETING_T0000000351.wav
+
+  ./zipformer/onnx_pretrained.py \
+    --encoder-model-filename $repo/exp/encoder-epoch-99-avg-1.int8.onnx \
+    --decoder-model-filename $repo/exp/decoder-epoch-99-avg-1.onnx \
+    --joiner-model-filename $repo/exp/joiner-epoch-99-avg-1.int8.onnx \
+    --tokens $repo/data/lang_bpe_2000/tokens.txt \
+    $repo/test_wavs/DEV_T0000000000.wav \
+    $repo/test_wavs/DEV_T0000000001.wav \
+    $repo/test_wavs/DEV_T0000000002.wav \
+    $repo/test_wavs/TEST_MEETING_T0000000113.wav \
+    $repo/test_wavs/TEST_MEETING_T0000000219.wav \
+    $repo/test_wavs/TEST_MEETING_T0000000351.wav
+
+  ./zipformer/onnx_pretrained.py \
+    --encoder-model-filename $repo/exp/encoder-epoch-99-avg-1.fp16.onnx \
+    --decoder-model-filename $repo/exp/decoder-epoch-99-avg-1.fp16.onnx \
+    --joiner-model-filename $repo/exp/joiner-epoch-99-avg-1.fp16.onnx \
+    --tokens $repo/data/lang_bpe_2000/tokens.txt \
+    $repo/test_wavs/DEV_T0000000000.wav \
+    $repo/test_wavs/DEV_T0000000001.wav \
+    $repo/test_wavs/DEV_T0000000002.wav \
+    $repo/test_wavs/TEST_MEETING_T0000000113.wav \
+    $repo/test_wavs/TEST_MEETING_T0000000219.wav \
+    $repo/test_wavs/TEST_MEETING_T0000000351.wav
+
+  rm -rf $repo
+}
+
+function run_2023_11_05_streaming() {
+  repo_url=https://huggingface.co/zrjin/icefall-asr-multi-zh-hans-zipformer-ctc-streaming-2023-11-05
+  log "Downloading pre-trained model from $repo_url"
+  GIT_LFS_SKIP_SMUDGE=1 git clone $repo_url
+  repo=$(basename $repo_url)
+
+  pushd $repo
+  cd exp/
+  git lfs pull --include pretrained.pt
+  rm -fv epoch-20.pt
+  rm -fv *.onnx
+  ln -s pretrained.pt epoch-20.pt
+  cd ../data/lang_bpe_2000
+  ls -lh
+  git lfs pull --include L.pt L_disambig.pt Linv.pt bpe.model
+  git lfs pull --include "*.model"
+  ls -lh
+  popd
+
+  log "----------------------------------------"
+  log "Export streaming ONNX CTC models "
+  log "----------------------------------------"
+  ./zipformer/export-onnx-streaming-ctc.py \
+    --exp-dir $repo/exp \
+    --tokens $repo/data/lang_bpe_2000/tokens.txt \
+    --causal 1 \
+    --avg 1 \
+    --epoch 20 \
+    --use-averaged-model 0 \
+    --chunk-size 16 \
+    --left-context-frames 128 \
+    --use-ctc 1 \
+    --fp16 1
+
+  ls -lh $repo/exp/
+
+  log "------------------------------------------------------------"
+  log "Test exported streaming ONNX CTC models (greedy search)     "
+  log "------------------------------------------------------------"
+
+  test_wavs=(
+    DEV_T0000000000.wav
+    DEV_T0000000001.wav
+    DEV_T0000000002.wav
+    TEST_MEETING_T0000000113.wav
+    TEST_MEETING_T0000000219.wav
+    TEST_MEETING_T0000000351.wav
+  )
+
+  for w in ${test_wavs[@]}; do
+    log "----fp32----"
+    ./zipformer/onnx_pretrained-streaming-ctc.py \
+      --model-filename $repo/exp/ctc-epoch-20-avg-1-chunk-16-left-128.onnx \
+      --tokens $repo/data/lang_bpe_2000/tokens.txt \
+      $repo/test_wavs/$w
+
+    log "----int8----"
+
+    ./zipformer/onnx_pretrained-streaming-ctc.py \
+      --model-filename $repo/exp/ctc-epoch-20-avg-1-chunk-16-left-128.int8.onnx \
+      --tokens $repo/data/lang_bpe_2000/tokens.txt \
+      $repo/test_wavs/$w
+
+    log "----fp16----"
+
+    ./zipformer/onnx_pretrained-streaming-ctc.py \
+      --model-filename $repo/exp/ctc-epoch-20-avg-1-chunk-16-left-128.fp16.onnx \
+      --tokens $repo/data/lang_bpe_2000/tokens.txt \
+      $repo/test_wavs/$w
+  done
+
+  log "Upload onnx CTC models to huggingface"
+  name=(
+    sherpa-onnx-streaming-zipformer-ctc-multi-zh-hans-2023-12-13
+    sherpa-onnx-streaming-zipformer-ctc-multi-zh-hans-int8-2023-12-13
+    sherpa-onnx-streaming-zipformer-ctc-multi-zh-hans-fp16-2023-12-13
+    )
+  for n in ${name[@]}; do
+      url=https://huggingface.co/k2-fsa/$n
+      GIT_LFS_SKIP_SMUDGE=1 git clone $url
+      dst=$(basename $url)
+      if [[ $n == sherpa-onnx-streaming-zipformer-ctc-multi-zh-hans-2023-12-13 ]]; then
+        cp -v $repo/exp/ctc-epoch-20-avg-1-chunk-16-left-128.onnx $dst
+      elif [[ $n == sherpa-onnx-streaming-zipformer-ctc-multi-zh-hans-int8-2023-12-13 ]]; then
+        cp -v $repo/exp/ctc-epoch-20-avg-1-chunk-16-left-128.int8.onnx $dst
+      elif [[ $n == sherpa-onnx-streaming-zipformer-ctc-multi-zh-hans-fp16-2023-12-13 ]]; then
+        cp -v $repo/exp/ctc-epoch-20-avg-1-chunk-16-left-128.fp16.onnx $dst
+      fi
+
+      cp -v $repo/data/lang_bpe_2000/tokens.txt $dst
+      cp -v $repo/data/lang_bpe_2000/bpe.model $dst
+      mkdir -p $dst/test_wavs
+      cp -v $repo/test_wavs/*.wav $dst/test_wavs
+      cd $dst
+      git lfs track "*.onnx" "bpe.model" "*.wav"
+      ls -lh
+      file bpe.model
+      git status
+      git add .
+      git commit -m "upload model" && git push https://k2-fsa:${HF_TOKEN}@huggingface.co/k2-fsa/$dst main || true
+
+      log "Upload models to https://github.com/k2-fsa/sherpa-onnx"
+      rm -rf .git
+      rm -fv .gitattributes
+      cd ..
+      tar cjfv $dst.tar.bz2 $dst
+      ls -lh *.tar.bz2
+      mv -v $dst.tar.bz2 ../../../
+  done
+
+  log "----------------------------------------"
+  log "Export streaming ONNX transducer models "
+  log "----------------------------------------"
+
+  ./zipformer/export-onnx-streaming.py \
+    --exp-dir $repo/exp \
+    --tokens $repo/data/lang_bpe_2000/tokens.txt \
+    --causal 1 \
+    --avg 1 \
+    --epoch 20 \
+    --use-averaged-model 0 \
+    --chunk-size 16 \
+    --left-context-frames 128 \
+    --use-ctc 0 \
+    --fp16 1
+
+  ls -lh $repo/exp
+
+  log "------------------------------------------------------------"
+  log "Test exported streaming ONNX transducer models (Python code)"
+  log "------------------------------------------------------------"
+
+  log "test fp32"
+  ./zipformer/onnx_pretrained-streaming.py \
+    --encoder-model-filename $repo/exp/encoder-epoch-20-avg-1-chunk-16-left-128.onnx \
+    --decoder-model-filename $repo/exp/decoder-epoch-20-avg-1-chunk-16-left-128.onnx \
+    --joiner-model-filename $repo/exp/joiner-epoch-20-avg-1-chunk-16-left-128.onnx \
+    --tokens $repo/data/lang_bpe_2000/tokens.txt \
+    $repo/test_wavs/DEV_T0000000000.wav
+
+  log "test int8"
+  ./zipformer/onnx_pretrained-streaming.py \
+    --encoder-model-filename $repo/exp/encoder-epoch-20-avg-1-chunk-16-left-128.int8.onnx \
+    --decoder-model-filename $repo/exp/decoder-epoch-20-avg-1-chunk-16-left-128.onnx \
+    --joiner-model-filename $repo/exp/joiner-epoch-20-avg-1-chunk-16-left-128.int8.onnx \
+    --tokens $repo/data/lang_bpe_2000/tokens.txt \
+    $repo/test_wavs/DEV_T0000000000.wav
+
+  log "test fp16"
+  ./zipformer/onnx_pretrained-streaming.py \
+    --encoder-model-filename $repo/exp/encoder-epoch-20-avg-1-chunk-16-left-128.fp16.onnx \
+    --decoder-model-filename $repo/exp/decoder-epoch-20-avg-1-chunk-16-left-128.fp16.onnx \
+    --joiner-model-filename $repo/exp/joiner-epoch-20-avg-1-chunk-16-left-128.fp16.onnx \
+    --tokens $repo/data/lang_bpe_2000/tokens.txt \
+    $repo/test_wavs/DEV_T0000000000.wav
+
+  name=(
+    sherpa-onnx-streaming-zipformer-multi-zh-hans-2023-12-13
+    sherpa-onnx-streaming-zipformer-multi-zh-hans-int8-2023-12-13
+    sherpa-onnx-streaming-zipformer-multi-zh-hans-fp16-2023-12-13
+  )
+
+  for n in ${name[@]}; do
+      url=https://huggingface.co/csukuangfj/$n
+      GIT_LFS_SKIP_SMUDGE=1 git clone $url
+      dst=$(basename $url)
+      if [[ $n == sherpa-onnx-streaming-zipformer-multi-zh-hans-2023-12-13 ]]; then
+        cp -v $repo/exp/encoder-epoch-20-avg-1-chunk-16-left-128.onnx $dst
+        cp -v $repo/exp/decoder-epoch-20-avg-1-chunk-16-left-128.onnx $dst
+        cp -v $repo/exp/joiner-epoch-20-avg-1-chunk-16-left-128.onnx $dst
+      elif [[ $n == sherpa-onnx-streaming-zipformer-multi-zh-hans-int8-2023-12-13 ]]; then
+        cp -v $repo/exp/encoder-epoch-20-avg-1-chunk-16-left-128.int8.onnx $dst
+        cp -v $repo/exp/decoder-epoch-20-avg-1-chunk-16-left-128.onnx $dst
+        cp -v $repo/exp/joiner-epoch-20-avg-1-chunk-16-left-128.int8.onnx $dst
+      elif [[ $n == sherpa-onnx-streaming-zipformer-multi-zh-hans-fp16-2023-12-13 ]]; then
+        cp -v $repo/exp/encoder-epoch-20-avg-1-chunk-16-left-128.fp16.onnx $dst
+        cp -v $repo/exp/decoder-epoch-20-avg-1-chunk-16-left-128.fp16.onnx $dst
+        cp -v $repo/exp/joiner-epoch-20-avg-1-chunk-16-left-128.fp16.onnx $dst
+      fi
+
+      cp -v $repo/data/lang_bpe_2000/tokens.txt $dst
+      cp -v $repo/data/lang_bpe_2000/bpe.model $dst
+      mkdir -p $dst/test_wavs
+      cp -v $repo/test_wavs/*.wav $dst/test_wavs
+      cd $dst
+      git lfs track "*.onnx" "bpe.model" "*.wav"
+      ls -lh
+      file bpe.model
+      git status
+      git add .
+      git commit -m "upload model" && git push https://csukuangfj:${HF_TOKEN}@huggingface.co/csukuangfj/$dst main || true
+
+      log "Upload models to https://github.com/k2-fsa/sherpa-onnx"
+      rm -rf .git
+      rm -fv .gitattributes
+      cd ..
+      tar cjfv $dst.tar.bz2 $dst
+      ls -lh *.tar.bz2
+      mv -v $dst.tar.bz2 ../../../
+  done
+}
+
+function run_2023_12_12_streaming() {
+  log "Upload onnx transducer models to huggingface"
+
+  url=https://huggingface.co/k2-fsa/sherpa-onnx-streaming-zipformer-multi-zh-hans-2023-12-12
+  GIT_LFS_SKIP_SMUDGE=1 git clone $url
+  dst=$(basename $url)
+  cp -v $repo/exp/encoder*.onnx $dst
+  cp -v $repo/exp/decoder*.onnx $dst
+  cp -v $repo/exp/joiner*.onnx $dst
+  cp -v $repo/data/lang_bpe_2000/tokens.txt $dst
+  cp -v $repo/data/lang_bpe_2000/bpe.model $dst
+  mkdir -p $dst/test_wavs
+  cp -v $repo/test_wavs/*.wav $dst/test_wavs
+  cd $dst
+  git lfs track "*.onnx" bpe.model "*.wav"
+  git add .
+  git commit -m "upload model" && git push https://k2-fsa:${HF_TOKEN}@huggingface.co/k2-fsa/$dst main || true
+
+  log "Upload models to https://github.com/k2-fsa/sherpa-onnx"
+  rm -rf .git
+  rm -fv .gitattributes
+  cd ..
+  tar cjfv $dst.tar.bz2 $dst
+  ls -lh *.tar.bz2
+  mv -v $dst.tar.bz2 ../../../
+}
+
+function run_yuekai_large() {
+  repo_url=https://csukuangfj:${HF_TOKEN}@huggingface.co/yuekai/icefall-asr-multi-zh-hans-zipformer-large
+  log "Downloading pre-trained model from $repo_url"
+  GIT_LFS_SKIP_SMUDGE=1 git clone $repo_url
+  repo=$(basename $repo_url)
+  pushd $repo
+  git lfs pull --include pretrained.pt
+  mv pretrained.pt epoch-99.pt
+  curl -SL -O https://huggingface.co/pingzxy/icefall-asr-multi-zh-hans-zipformer-large-onnx/resolve/main/tokens.txt
+  popd
+
+  log "----------------------------------------"
+  log "Export streaming ONNX CTC models "
+  log "----------------------------------------"
+  ./zipformer/export-onnx-streaming-ctc.py \
+    --exp-dir $repo/ \
+    --tokens $repo/tokens.txt \
+    --causal 1 \
+    --avg 1 \
+    --epoch 99 \
+    --use-averaged-model 0 \
+    --chunk-size 16 \
+    --left-context-frames 128 \
+    --use-ctc 1 \
+    \
+    --num-encoder-layers 2,2,4,5,4,2 \
+    --feedforward-dim 768,1024,1536,2048,1536,768 \
+    --encoder-dim 256,384,512,768,512,256 \
+    --encoder-unmasked-dim 192,192,256,320,256,192 \
+    \
+    --fp16 1 \
+    --use-whisper-features 1
+
+
+  ls -lh $repo/
+  pushd $repo
+
+cat >README.md <<EOF
+# Introduction
+
+This model is converted
+from
+https://huggingface.co/yuekai/icefall-asr-multi-zh-hans-zipformer-large
+
+The training code can be found at
+https://github.com/k2-fsa/icefall/blob/master/egs/multi_zh-hans/ASR/RESULTS.md#multi-chinese-datasets-char-based-training-results-streaming-on-zipformer-large-model
+EOF
+
+  mv -v ctc-epoch-99-avg-1-chunk-16-left-128.fp16.onnx model.fp16.onnx
+  mv -v ctc-epoch-99-avg-1-chunk-16-left-128.int8.onnx model.int8.onnx
+  mv -v ctc-epoch-99-avg-1-chunk-16-left-128.onnx model.onnx
+
+  ls -lh *.onnx
+
+  mkdir test_wavs
+  cd test_wavs
+  curl -SL -O https://huggingface.co/csukuangfj/sherpa-onnx-streaming-zipformer-small-ctc-zh-int8-2025-04-01/resolve/main/test_wavs/0.wav
+  curl -SL -O https://huggingface.co/csukuangfj/sherpa-onnx-streaming-zipformer-small-ctc-zh-int8-2025-04-01/resolve/main/test_wavs/1.wav
+  curl -SL -O https://huggingface.co/csukuangfj/sherpa-onnx-streaming-zipformer-small-ctc-zh-int8-2025-04-01/resolve/main/test_wavs/8k.wav
+  popd
+
+  for w in 0.wav 1.wav 8k.wav; do
+    log "---fp32---"
+    sherpa-onnx \
+      --zipformer2-ctc-model=$repo/model.onnx \
+      --tokens=$repo/tokens.txt \
+      $repo/test_wavs/$w
+
+    log "---int8---"
+
+    sherpa-onnx \
+      --zipformer2-ctc-model=$repo/model.int8.onnx \
+      --tokens=$repo/tokens.txt \
+      $repo/test_wavs/$w
+
+    log "---fp16---"
+
+    sherpa-onnx \
+      --zipformer2-ctc-model=$repo/model.fp16.onnx \
+      --tokens=$repo/tokens.txt \
+      $repo/test_wavs/$w
+  done
+
+  name=(
+    sherpa-onnx-streaming-zipformer-ctc-zh-2025-06-30
+    sherpa-onnx-streaming-zipformer-ctc-zh-int8-2025-06-30
+    sherpa-onnx-streaming-zipformer-ctc-zh-fp16-2025-06-30
+  )
+  for n in ${name[@]}; do
+      url=https://huggingface.co/csukuangfj/$n
+      GIT_LFS_SKIP_SMUDGE=1 git clone $url
+      dst=$(basename $url)
+      if [[ $n == sherpa-onnx-streaming-zipformer-ctc-zh-2025-06-30 ]]; then
+        cp -v $repo/model.onnx $dst
+      elif [[ $n == sherpa-onnx-streaming-zipformer-ctc-zh-int8-2025-06-30 ]]; then
+        cp -v $repo/model.int8.onnx $dst
+      elif [[ $n == sherpa-onnx-streaming-zipformer-ctc-zh-fp16-2025-06-30 ]]; then
+        cp -v $repo/model.fp16.onnx $dst
+      fi
+
+      cp -v $repo/tokens.txt $dst
+      cp -v $repo/README.md $dst
+      mkdir -p $dst/test_wavs
+      cp -v $repo/test_wavs/*.wav $dst/test_wavs
+      cd $dst
+      git lfs track "*.onnx" "*.wav"
+      ls -lh
+      git status
+      git add .
+      git commit -m "upload model" && git push https://csukuangfj:${HF_TOKEN}@huggingface.co/csukuangfj/$dst main || true
+
+      log "Upload models to https://github.com/k2-fsa/sherpa-onnx"
+      rm -rf .git
+      rm -fv .gitattributes
+      cd ..
+      tar cjfv $dst.tar.bz2 $dst
+      ls -lh *.tar.bz2
+      mv -v $dst.tar.bz2 ../../../
+  done
+
+  rm $repo/*.onnx
+
+  log "----------------------------------------"
+  log "Export streaming ONNX transducer models "
+  log "----------------------------------------"
+
+  ./zipformer/export-onnx-streaming.py \
+    --exp-dir $repo \
+    --tokens $repo/tokens.txt \
+    --causal 1 \
+    --avg 1 \
+    --epoch 99 \
+    --use-averaged-model 0 \
+    --chunk-size 16 \
+    --left-context-frames 128 \
+    --use-ctc 0 \
+    \
+    --num-encoder-layers 2,2,4,5,4,2 \
+    --feedforward-dim 768,1024,1536,2048,1536,768 \
+    --encoder-dim 256,384,512,768,512,256 \
+    --encoder-unmasked-dim 192,192,256,320,256,192 \
+    \
+    --fp16 1 \
+    --use-whisper-features 1
+
+  ls -lh $repo
+  pushd $repo
+  for m in encoder decoder joiner; do
+    mv -v $m-epoch-99-avg-1-chunk-16-left-128.onnx $m.onnx
+    mv -v $m-epoch-99-avg-1-chunk-16-left-128.fp16.onnx $m.fp16.onnx
+    mv -v $m-epoch-99-avg-1-chunk-16-left-128.int8.onnx $m.int8.onnx
+  done
+  ls -lh *.onnx
+  popd
+
+  for w in 0.wav 1.wav 8k.wav; do
+    log "---fp32---"
+      sherpa-onnx \
+        --encoder=$repo/encoder.onnx \
+        --decoder=$repo/decoder.onnx \
+        --joiner=$repo/joiner.onnx \
+        --tokens=$repo/tokens.txt \
+        $repo/test_wavs/$w
+
+    log "---int8---"
+
+      sherpa-onnx \
+        --encoder=$repo/encoder.int8.onnx \
+        --decoder=$repo/decoder.onnx \
+        --joiner=$repo/joiner.int8.onnx \
+        --tokens=$repo/tokens.txt \
+        $repo/test_wavs/$w
+
+    log "---fp16---"
+
+      sherpa-onnx \
+        --encoder=$repo/encoder.fp16.onnx \
+        --decoder=$repo/decoder.fp16.onnx \
+        --joiner=$repo/joiner.fp16.onnx \
+        --tokens=$repo/tokens.txt \
+        $repo/test_wavs/$w
+  done
+
+  name=(
+    sherpa-onnx-streaming-zipformer-zh-2025-06-30
+    sherpa-onnx-streaming-zipformer-zh-int8-2025-06-30
+    sherpa-onnx-streaming-zipformer-zh-fp16-2025-06-30
+  )
+  for n in ${name[@]}; do
+      url=https://huggingface.co/csukuangfj/$n
+      GIT_LFS_SKIP_SMUDGE=1 git clone $url
+      dst=$(basename $url)
+      if [[ $n == sherpa-onnx-streaming-zipformer-zh-2025-06-30 ]]; then
+        cp -v $repo/encoder.onnx $dst
+        cp -v $repo/decoder.onnx $dst
+        cp -v $repo/joiner.onnx $dst
+      elif [[ $n == sherpa-onnx-streaming-zipformer-zh-int8-2025-06-30 ]]; then
+        cp -v $repo/encoder.int8.onnx $dst
+        cp -v $repo/decoder.onnx $dst
+        cp -v $repo/joiner.int8.onnx $dst
+      elif [[ $n == sherpa-onnx-streaming-zipformer-zh-fp16-2025-06-30 ]]; then
+        cp -v $repo/encoder.fp16.onnx $dst
+        cp -v $repo/decoder.fp16.onnx $dst
+        cp -v $repo/joiner.fp16.onnx $dst
+      fi
+
+      cp -v $repo/tokens.txt $dst
+      cp -v $repo/README.md $dst
+      mkdir -p $dst/test_wavs
+      cp -v $repo/test_wavs/*.wav $dst/test_wavs
+      cd $dst
+      git lfs track "*.onnx" "*.wav"
+      ls -lh
+      git status
+      git add .
+      git commit -m "upload model" && git push https://csukuangfj:${HF_TOKEN}@huggingface.co/csukuangfj/$dst main || true
+
+      log "Upload models to https://github.com/k2-fsa/sherpa-onnx"
+      rm -rf .git
+      rm -fv .gitattributes
+      cd ..
+      tar cjfv $dst.tar.bz2 $dst
+      ls -lh *.tar.bz2
+      mv -v $dst.tar.bz2 ../../../
+  done
+}
+
+function run_yuekai_xl() {
+  repo_url=https://csukuangfj:${HF_TOKEN}@huggingface.co/yuekai/icefall-asr-multi-zh-hans-zipformer-xl
+  log "Downloading pre-trained model from $repo_url"
+  GIT_LFS_SKIP_SMUDGE=1 git clone $repo_url
+  repo=$(basename $repo_url)
+
+  pushd $repo
+  git lfs pull --include pretrained.pt
+  git lfs pull --include data/lang_bpe_2000/bpe.model
+  mv pretrained.pt epoch-99.pt
+  ls -lh *.pt
+  popd
+
+  log "----------------------------------------"
+  log "Export streaming ONNX CTC models "
+  log "----------------------------------------"
+  ./zipformer/export-onnx-streaming-ctc.py \
+    --exp-dir $repo/ \
+    --tokens $repo/data/lang_bpe_2000/tokens.txt \
+    --causal 1 \
+    --avg 1 \
+    --epoch 99 \
+    --use-averaged-model 0 \
+    --chunk-size 16 \
+    --left-context-frames 128 \
+    --use-ctc 1 \
+    \
+    --num-encoder-layers 2,3,5,6,5,3 \
+    --feedforward-dim 1536,2048,3072,4096,3072,1536 \
+    --encoder-dim 512,768,1024,1536,1024,512 \
+    --encoder-unmasked-dim 192,192,256,320,256,192 \
+    --decoder-dim 768 --joiner-dim 768 \
+    --value-head-dim 18 \
+    --query-head-dim 48 \
+    --num-heads 4,4,4,8,4,4 \
+    \
+    --fp16 1 \
+    --use-whisper-features 1 \
+    --use-external-data 1
+
+  mv -v ctc-epoch-99-avg-1-chunk-16-left-128.int8.onnx model.int8.onnx
+  mv -v ctc-epoch-99-avg-1-chunk-16-left-128.fp16.onnx model.fp16.onnx
+
+  ls -lh *.onnx
+
+  mkdir test_wavs
+  pushd test_wavs
+  curl -SL -O https://huggingface.co/csukuangfj/sherpa-onnx-streaming-zipformer-small-ctc-zh-int8-2025-04-01/resolve/main/test_wavs/0.wav
+  curl -SL -O https://huggingface.co/csukuangfj/sherpa-onnx-streaming-zipformer-small-ctc-zh-int8-2025-04-01/resolve/main/test_wavs/1.wav
+  curl -SL -O https://huggingface.co/csukuangfj/sherpa-onnx-streaming-zipformer-small-ctc-zh-int8-2025-04-01/resolve/main/test_wavs/8k.wav
+  popd
+
+  for w in 0.wav 1.wav 8k.wav; do
+    log "---int8---"
+
+    sherpa-onnx \
+      --zipformer2-ctc-model=./model.int8.onnx \
+      --tokens=$repo/data/lang_bpe_2000/tokens.txt \
+      test_wavs/$w
+
+    log "---fp16---"
+
+    sherpa-onnx \
+      --zipformer2-ctc-model=./model.fp16.onnx \
+      --tokens=$repo/data/lang_bpe_2000/tokens.txt \
+      test_wavs/$w
+  done
+
+  pushd $repo
+cat >README.md <<EOF
+# Introduction
+
+This model is converted
+from
+https://huggingface.co/yuekai/icefall-asr-multi-zh-hans-zipformer-xl
+
+The training code can be found at
+https://github.com/k2-fsa/icefall/blob/master/egs/multi_zh-hans/ASR/RESULTS.md#multi-chinese-datasets-char-based-training-results-streaming-on-zipformer-xl-model
+EOF
+  popd
+
+  name=(
+    sherpa-onnx-streaming-zipformer-ctc-zh-xlarge-int8-2025-06-30
+    sherpa-onnx-streaming-zipformer-ctc-zh-xlarge-fp16-2025-06-30
+  )
+
+  for n in ${name[@]}; do
+      url=https://huggingface.co/csukuangfj/$n
+      GIT_LFS_SKIP_SMUDGE=1 git clone $url
+      dst=$(basename $url)
+      if [[ $n == sherpa-onnx-streaming-zipformer-ctc-zh-xlarge-fp16-2025-06-30 ]]; then
+        cp -v model.fp16.onnx $dst
+      elif [[ $n == sherpa-onnx-streaming-zipformer-ctc-zh-xlarge-int8-2025-06-30 ]]; then
+        cp -v model.int8.onnx $dst
+      fi
+
+      cp -v $repo/data/lang_bpe_2000/tokens.txt $dst
+      cp -v $repo/data/lang_bpe_2000/bpe.model $dst
+      cp -v $repo/README.md $dst
+      mkdir -p $dst/test_wavs
+      cp -v ./test_wavs/*.wav $dst/test_wavs
+      cd $dst
+      git lfs track "*.onnx" "*.wav" "bpe.model"
+      ls -lh
+      git status
+      git add .
+      git commit -m "upload model" && git push https://csukuangfj:${HF_TOKEN}@huggingface.co/csukuangfj/$dst main || true
+
+      log "Upload models to https://github.com/k2-fsa/sherpa-onnx"
+      rm -rf .git
+      rm -fv .gitattributes
+      cd ..
+
+      ls -lh $dst
+      tar cjfv $dst.tar.bz2 $dst
+      ls -lh *.tar.bz2
+      mv -v $dst.tar.bz2 ../../../
+  done
+
+  rm -fv *.onnx *.weights
+
+  log "----------------------------------------"
+  log "Export streaming ONNX transducer models "
+  log "----------------------------------------"
+
+  ./zipformer/export-onnx-streaming.py \
+    --exp-dir $repo/ \
+    --tokens $repo/data/lang_bpe_2000/tokens.txt \
+    --causal 1 \
+    --avg 1 \
+    --epoch 99 \
+    --use-averaged-model 0 \
+    --chunk-size 16 \
+    --left-context-frames 128 \
+    --use-ctc 0 \
+    \
+    --num-encoder-layers 2,3,5,6,5,3 \
+    --feedforward-dim 1536,2048,3072,4096,3072,1536 \
+    --encoder-dim 512,768,1024,1536,1024,512 \
+    --encoder-unmasked-dim 192,192,256,320,256,192 \
+    --decoder-dim 768 --joiner-dim 768 \
+    --value-head-dim 18 \
+    --query-head-dim 48 \
+    --num-heads 4,4,4,8,4,4 \
+    \
+    --fp16 1 \
+    --use-whisper-features 1 \
+    --use-external-data 1
+
+    ls -lh *.onnx
+    ls -lh *.weights
+
+    mv encoder-epoch-99-avg-1-chunk-16-left-128.fp16.onnx encoder.fp16.onnx
+    mv encoder-epoch-99-avg-1-chunk-16-left-128.int8.onnx encoder.int8.onnx
+
+    mv $repo/decoder-epoch-99-avg-1-chunk-16-left-128.onnx decoder.onnx
+    mv $repo/decoder-epoch-99-avg-1-chunk-16-left-128.fp16.onnx decoder.fp16.onnx
+
+    mv $repo/joiner-epoch-99-avg-1-chunk-16-left-128.int8.onnx joiner.int8.onnx
+    mv $repo/joiner-epoch-99-avg-1-chunk-16-left-128.fp16.onnx joiner.fp16.onnx
+
+  name=(
+    sherpa-onnx-streaming-zipformer-zh-xlarge-int8-2025-06-30
+    sherpa-onnx-streaming-zipformer-zh-xlarge-fp16-2025-06-30
+  )
+
+  for n in ${name[@]}; do
+      url=https://huggingface.co/csukuangfj/$n
+      GIT_LFS_SKIP_SMUDGE=1 git clone $url
+      dst=$(basename $url)
+      if [[ $n == sherpa-onnx-streaming-zipformer-zh-xlarge-fp16-2025-06-30 ]]; then
+        cp -v encoder.fp16.onnx $dst
+        cp -v decoder.fp16.onnx $dst
+        cp -v joiner.fp16.onnx $dst
+      elif [[ $n == sherpa-onnx-streaming-zipformer-zh-xlarge-int8-2025-06-30 ]]; then
+        cp -v encoder.int8.onnx $dst
+        cp -v decoder.onnx $dst
+        cp -v joiner.int8.onnx $dst
+      fi
+
+      cp -v $repo/data/lang_bpe_2000/tokens.txt $dst
+      cp -v $repo/data/lang_bpe_2000/bpe.model $dst
+      cp -v $repo/README.md $dst
+      mkdir -p $dst/test_wavs
+      cp -v ./test_wavs/*.wav $dst/test_wavs
+      cd $dst
+      git lfs track "*.onnx" "*.wav" "bpe.model"
+      ls -lh
+      git status
+      git add .
+      git commit -m "upload model" && git push https://csukuangfj:${HF_TOKEN}@huggingface.co/csukuangfj/$dst main || true
+
+      log "Upload models to https://github.com/k2-fsa/sherpa-onnx"
+      rm -rf .git
+      rm -fv .gitattributes
+      cd ..
+
+      ls -lh $dst
+      tar cjfv $dst.tar.bz2 $dst
+      ls -lh *.tar.bz2
+      mv -v $dst.tar.bz2 ../../../
+  done
+
+  rm -fv *.onnx *.weights
+}
+
+# run_yuekai_large
+# run_yuekai_xl
+# run_2023_9_2
+run_2023_11_05_streaming
+# run_2023_12_12_streaming
diff --git a/.github/workflows/multi-zh-hans.yml b/.github/workflows/multi-zh-hans.yml
index 9081047de..4da0a784a 100644
--- a/.github/workflows/multi-zh-hans.yml
+++ b/.github/workflows/multi-zh-hans.yml
@@ -1,4 +1,4 @@
-name: run-multi-zh-hans
+name: multi-zh-hans
 
 on:
   push:
@@ -8,65 +8,72 @@ on:
   workflow_dispatch:
 
 concurrency:
-  group: run-multi-zh-hans-${{ github.ref }}
+  group: multi-zh-hans-${{ github.ref }}
   cancel-in-progress: true
 
 permissions:
   contents: write
 
 jobs:
+  generate_build_matrix:
+    if: github.repository_owner == 'csukuangfj' || github.repository_owner == 'k2-fsa'
+    # see https://github.com/pytorch/pytorch/pull/50633
+    runs-on: ubuntu-latest
+    outputs:
+      matrix: ${{ steps.set-matrix.outputs.matrix }}
+    steps:
+      - uses: actions/checkout@v4
+        with:
+          fetch-depth: 0
+      - name: Generating build matrix
+        id: set-matrix
+        run: |
+          # outputting for debugging purposes
+          python ./.github/scripts/docker/generate_build_matrix.py --torch-version "2.7.0" --python-version "3.11"
+          MATRIX=$(python ./.github/scripts/docker/generate_build_matrix.py --torch-version "2.7.0" --python-version "3.11")
+          echo "::set-output name=matrix::${MATRIX}"
   multi-zh-hans:
-    runs-on: ${{ matrix.os }}
+    needs: generate_build_matrix
+    name: py${{ matrix.python-version }} torch${{ matrix.torch-version }} v${{ matrix.version }}
+    runs-on: ubuntu-latest
     strategy:
       fail-fast: false
       matrix:
-        os: [ubuntu-latest]
-        python-version: [3.8]
+        ${{ fromJson(needs.generate_build_matrix.outputs.matrix) }}
 
     steps:
       - uses: actions/checkout@v4
         with:
           fetch-depth: 0
 
-      - name: Setup Python ${{ matrix.python-version }}
-        uses: actions/setup-python@v2
-        with:
-          python-version: ${{ matrix.python-version }}
-          cache: 'pip'
-          cache-dependency-path: '**/requirements-ci.txt'
-
-      - name: Install Python dependencies
-        run: |
-          grep -v '^#' ./requirements-ci.txt  | xargs -n 1 -L 1 pip install
-          pip uninstall -y protobuf
-          pip install --no-binary protobuf protobuf==3.20.*
-
-      - name: Cache kaldifeat
-        id: my-cache
-        uses: actions/cache@v2
-        with:
-          path: |
-            ~/tmp/kaldifeat
-          key: cache-tmp-${{ matrix.python-version }}-2023-05-22
-
-      - name: Install kaldifeat
-        if: steps.my-cache.outputs.cache-hit != 'true'
+      - name: Free space
         shell: bash
         run: |
-          .github/scripts/install-kaldifeat.sh
+          df -h
+          rm -rf /opt/hostedtoolcache
+          df -h
+          echo "pwd: $PWD"
+          echo "github.workspace ${{ github.workspace }}"
 
-      - name: export-model
+      - name: Test with multi_zh-hans
+        uses: addnab/docker-run-action@v3
+        with:
+            image: ghcr.io/${{ github.repository_owner }}/icefall:cpu-py${{ matrix.python-version }}-torch${{ matrix.torch-version }}-v${{ matrix.version }}
+            options: |
+              --volume ${{ github.workspace }}/:/icefall
+            shell: bash
+            run: |
+              export PYTHONPATH=/icefall:$PYTHONPATH
+              export HF_TOKEN=${{ secrets.HF_TOKEN }}
+              cd /icefall
+              git config --global --add safe.directory /icefall
+
+              .github/scripts/multi_zh-hans/ASR/run.sh
+
+      - name: Show models
         shell: bash
-        env:
-          HF_TOKEN: ${{ secrets.HF_TOKEN }}
         run: |
-          sudo apt-get -qq install git-lfs tree
-          export PYTHONPATH=$PWD:$PYTHONPATH
-          export PYTHONPATH=~/tmp/kaldifeat/kaldifeat/python:$PYTHONPATH
-          export PYTHONPATH=~/tmp/kaldifeat/build/lib:$PYTHONPATH
-
-          .github/scripts/multi-zh-hans.sh
-          ls -lh
+          ls -lh *.tar.bz2
 
       - name: upload model to https://github.com/k2-fsa/sherpa-onnx
         uses: svenstaro/upload-release-action@v2
diff --git a/egs/librispeech/ASR/zipformer/export-onnx-ctc.py b/egs/librispeech/ASR/zipformer/export-onnx-ctc.py
index 99685f2fe..413b5bb1e 100755
--- a/egs/librispeech/ASR/zipformer/export-onnx-ctc.py
+++ b/egs/librispeech/ASR/zipformer/export-onnx-ctc.py
@@ -153,6 +153,13 @@ def get_parser():
         help="The context size in the decoder. 1 means bigram; 2 means tri-gram",
     )
 
+    parser.add_argument(
+        "--fp16",
+        type=str2bool,
+        default=False,
+        help="Whether to export models in fp16",
+    )
+
     add_model_arguments(parser)
 
     return parser
@@ -176,6 +183,15 @@ def add_meta_data(filename: str, meta_data: Dict[str, str]):
     onnx.save(model, filename)
 
 
+def export_onnx_fp16(onnx_fp32_path, onnx_fp16_path):
+    import onnxmltools
+    from onnxmltools.utils.float16_converter import convert_float_to_float16
+
+    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)
+
+
 class OnnxModel(nn.Module):
     """A wrapper for encoder_embed, Zipformer, and ctc_output layer"""
 
@@ -407,7 +423,7 @@ def main():
     opset_version = 13
 
     logging.info("Exporting ctc model")
-    filename = params.exp_dir / f"model.onnx"
+    filename = params.exp_dir / "model.onnx"
     export_ctc_model_onnx(
         model,
         filename,
@@ -420,7 +436,7 @@ def main():
 
     logging.info("Generate int8 quantization models")
 
-    filename_int8 = params.exp_dir / f"model.int8.onnx"
+    filename_int8 = params.exp_dir / "model.int8.onnx"
     quantize_dynamic(
         model_input=filename,
         model_output=filename_int8,
@@ -428,6 +444,10 @@ def main():
         weight_type=QuantType.QInt8,
     )
 
+    if params.fp16:
+        filename_fp16 = params.exp_dir / "model.fp16.onnx"
+        export_onnx_fp16(filename, filename_fp16)
+
 
 if __name__ == "__main__":
     formatter = "%(asctime)s %(levelname)s [%(filename)s:%(lineno)d] %(message)s"
diff --git a/egs/librispeech/ASR/zipformer/export-onnx-streaming-ctc.py b/egs/librispeech/ASR/zipformer/export-onnx-streaming-ctc.py
index 1eba6093b..003b4bf2c 100755
--- a/egs/librispeech/ASR/zipformer/export-onnx-streaming-ctc.py
+++ b/egs/librispeech/ASR/zipformer/export-onnx-streaming-ctc.py
@@ -136,12 +136,35 @@ def get_parser():
         help="The context size in the decoder. 1 means bigram; 2 means tri-gram",
     )
 
+    parser.add_argument(
+        "--use-whisper-features",
+        type=str2bool,
+        default=False,
+        help="True to use whisper features. Must match the one used in training",
+    )
+
+    parser.add_argument(
+        "--fp16",
+        type=str2bool,
+        default=False,
+        help="Whether to export models in fp16",
+    )
+
+    parser.add_argument(
+        "--use-external-data",
+        type=str2bool,
+        default=False,
+        help="Set it to true for model file size > 2GB",
+    )
+
     add_model_arguments(parser)
 
     return parser
 
 
-def add_meta_data(filename: str, meta_data: Dict[str, str]):
+def add_meta_data(
+    filename: str, meta_data: Dict[str, str], use_external_data: bool = False
+):
     """Add meta data to an ONNX model. It is changed in-place.
 
     Args:
@@ -150,13 +173,46 @@ def add_meta_data(filename: str, meta_data: Dict[str, str]):
       meta_data:
         Key-value pairs.
     """
+    filename = str(filename)
+
     model = onnx.load(filename)
     for key, value in meta_data.items():
         meta = model.metadata_props.add()
         meta.key = key
         meta.value = value
 
-    onnx.save(model, filename)
+    if use_external_data:
+        # For models file size > 2GB
+        external_filename = Path(filename).stem
+
+        onnx.save(
+            model,
+            filename,
+            save_as_external_data=True,
+            all_tensors_to_one_file=True,
+            location=external_filename + ".weights",
+        )
+    else:
+        onnx.save(model, filename)
+
+
+def export_onnx_fp16(onnx_fp32_path, onnx_fp16_path):
+    import onnxmltools
+    from onnxmltools.utils.float16_converter import convert_float_to_float16
+
+    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):
+    import onnxmltools
+    from onnxmltools.utils.float16_converter import convert_float_to_float16_model_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)
 
 
 class OnnxModel(nn.Module):
@@ -270,6 +326,8 @@ def export_streaming_ctc_model_onnx(
     model: OnnxModel,
     encoder_filename: str,
     opset_version: int = 11,
+    use_whisper_features: bool = False,
+    use_external_data: bool = False,
 ) -> None:
     model.encoder.__class__.forward = model.encoder.__class__.streaming_forward
 
@@ -367,6 +425,10 @@ def export_streaming_ctc_model_onnx(
         "value_head_dims": value_head_dims,
         "num_heads": num_heads,
     }
+
+    if use_whisper_features:
+        meta_data["feature"] = "whisper"
+
     logging.info(f"meta_data: {meta_data}")
 
     for i in range(len(init_state[:-2]) // 6):
@@ -411,7 +473,11 @@ def export_streaming_ctc_model_onnx(
         },
     )
 
-    add_meta_data(filename=encoder_filename, meta_data=meta_data)
+    add_meta_data(
+        filename=encoder_filename,
+        meta_data=meta_data,
+        use_external_data=use_external_data,
+    )
 
 
 @torch.no_grad()
@@ -542,11 +608,18 @@ def main():
     opset_version = 13
 
     logging.info("Exporting model")
-    model_filename = params.exp_dir / f"ctc-{suffix}.onnx"
+
+    if params.use_external_data:
+        model_filename = f"ctc-{suffix}.onnx"
+    else:
+        model_filename = params.exp_dir / f"ctc-{suffix}.onnx"
+
     export_streaming_ctc_model_onnx(
         model,
-        model_filename,
+        str(model_filename),
         opset_version=opset_version,
+        use_whisper_features=params.use_whisper_features,
+        use_external_data=params.use_external_data,
     )
     logging.info(f"Exported model to {model_filename}")
 
@@ -555,7 +628,11 @@ def main():
 
     logging.info("Generate int8 quantization models")
 
-    model_filename_int8 = params.exp_dir / f"ctc-{suffix}.int8.onnx"
+    if params.use_external_data:
+        model_filename_int8 = f"ctc-{suffix}.int8.onnx"
+    else:
+        model_filename_int8 = params.exp_dir / f"ctc-{suffix}.int8.onnx"
+
     quantize_dynamic(
         model_input=model_filename,
         model_output=model_filename_int8,
@@ -563,6 +640,14 @@ def main():
         weight_type=QuantType.QInt8,
     )
 
+    if params.fp16:
+        if params.use_external_data:
+            model_filename_fp16 = f"ctc-{suffix}.fp16.onnx"
+            export_onnx_fp16_large_2gb(model_filename, model_filename_fp16)
+        else:
+            model_filename_fp16 = params.exp_dir / f"ctc-{suffix}.fp16.onnx"
+            export_onnx_fp16(model_filename, model_filename_fp16)
+
 
 if __name__ == "__main__":
     formatter = "%(asctime)s %(levelname)s [%(filename)s:%(lineno)d] %(message)s"
diff --git a/egs/librispeech/ASR/zipformer/export-onnx-streaming.py b/egs/librispeech/ASR/zipformer/export-onnx-streaming.py
index a35eb5287..29541570b 100755
--- a/egs/librispeech/ASR/zipformer/export-onnx-streaming.py
+++ b/egs/librispeech/ASR/zipformer/export-onnx-streaming.py
@@ -162,12 +162,47 @@ def get_parser():
         help="Whether to export models in fp16",
     )
 
+    parser.add_argument(
+        "--use-whisper-features",
+        type=str2bool,
+        default=False,
+        help="True to use whisper features. Must match the one used in training",
+    )
+
+    parser.add_argument(
+        "--use-external-data",
+        type=str2bool,
+        default=False,
+        help="Set it to true for model file size > 2GB",
+    )
+
     add_model_arguments(parser)
 
     return parser
 
 
-def add_meta_data(filename: str, meta_data: Dict[str, str]):
+def export_onnx_fp16(onnx_fp32_path, onnx_fp16_path):
+    import onnxmltools
+    from onnxmltools.utils.float16_converter import convert_float_to_float16
+
+    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):
+    import onnxmltools
+    from onnxmltools.utils.float16_converter import convert_float_to_float16_model_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], use_external_data: bool = False
+):
     """Add meta data to an ONNX model. It is changed in-place.
 
     Args:
@@ -182,7 +217,19 @@ def add_meta_data(filename: str, meta_data: Dict[str, str]):
         meta.key = key
         meta.value = value
 
-    onnx.save(model, filename)
+    if use_external_data:
+        # For models file size > 2GB
+        external_filename = Path(filename).stem
+
+        onnx.save(
+            model,
+            filename,
+            save_as_external_data=True,
+            all_tensors_to_one_file=True,
+            location=external_filename + ".weights",
+        )
+    else:
+        onnx.save(model, filename)
 
 
 class OnnxEncoder(nn.Module):
@@ -342,6 +389,8 @@ def export_encoder_model_onnx(
     encoder_filename: str,
     opset_version: int = 11,
     feature_dim: int = 80,
+    use_whisper_features: bool = False,
+    use_external_data: bool = False,
 ) -> None:
     encoder_model.encoder.__class__.forward = (
         encoder_model.encoder.__class__.streaming_forward
@@ -441,6 +490,9 @@ def export_encoder_model_onnx(
         "value_head_dims": value_head_dims,
         "num_heads": num_heads,
     }
+    if use_whisper_features:
+        meta_data["feature"] = "whisper"
+
     logging.info(f"meta_data: {meta_data}")
 
     for i in range(len(init_state[:-2]) // 6):
@@ -485,7 +537,11 @@ def export_encoder_model_onnx(
         },
     )
 
-    add_meta_data(filename=encoder_filename, meta_data=meta_data)
+    add_meta_data(
+        filename=encoder_filename,
+        meta_data=meta_data,
+        use_external_data=use_external_data,
+    )
 
 
 def export_decoder_model_onnx(
@@ -728,12 +784,17 @@ def main():
     opset_version = 13
 
     logging.info("Exporting encoder")
-    encoder_filename = params.exp_dir / f"encoder-{suffix}.onnx"
+    if params.use_external_data:
+        encoder_filename = f"encoder-{suffix}.onnx"
+    else:
+        encoder_filename = params.exp_dir / f"encoder-{suffix}.onnx"
     export_encoder_model_onnx(
         encoder,
-        encoder_filename,
+        str(encoder_filename),
         opset_version=opset_version,
         feature_dim=params.feature_dim,
+        use_whisper_features=params.use_whisper_features,
+        use_external_data=params.use_external_data,
     )
     logging.info(f"Exported encoder to {encoder_filename}")
 
@@ -756,31 +817,31 @@ def main():
     logging.info(f"Exported joiner to {joiner_filename}")
 
     if params.fp16:
-        from onnxconverter_common import float16
-
         logging.info("Generate fp16 models")
 
-        encoder = onnx.load(encoder_filename)
-        encoder_fp16 = float16.convert_float_to_float16(encoder, keep_io_types=True)
-        encoder_filename_fp16 = params.exp_dir / f"encoder-{suffix}.fp16.onnx"
-        onnx.save(encoder_fp16, encoder_filename_fp16)
+        if params.use_external_data:
+            encoder_filename_fp16 = f"encoder-{suffix}.fp16.onnx"
+            export_onnx_fp16_large_2gb(encoder_filename, encoder_filename_fp16)
+        else:
+            encoder_filename_fp16 = params.exp_dir / f"encoder-{suffix}.fp16.onnx"
+            export_onnx_fp16(encoder_filename, encoder_filename_fp16)
 
-        decoder = onnx.load(decoder_filename)
-        decoder_fp16 = float16.convert_float_to_float16(decoder, keep_io_types=True)
         decoder_filename_fp16 = params.exp_dir / f"decoder-{suffix}.fp16.onnx"
-        onnx.save(decoder_fp16, decoder_filename_fp16)
+        export_onnx_fp16(decoder_filename, decoder_filename_fp16)
 
-        joiner = onnx.load(joiner_filename)
-        joiner_fp16 = float16.convert_float_to_float16(joiner, keep_io_types=True)
         joiner_filename_fp16 = params.exp_dir / f"joiner-{suffix}.fp16.onnx"
-        onnx.save(joiner_fp16, joiner_filename_fp16)
+        export_onnx_fp16(joiner_filename, joiner_filename_fp16)
 
     # Generate int8 quantization models
     # See https://onnxruntime.ai/docs/performance/model-optimizations/quantization.html#data-type-selection
 
     logging.info("Generate int8 quantization models")
 
-    encoder_filename_int8 = params.exp_dir / f"encoder-{suffix}.int8.onnx"
+    if params.use_external_data:
+        encoder_filename_int8 = f"encoder-{suffix}.int8.onnx"
+    else:
+        encoder_filename_int8 = params.exp_dir / f"encoder-{suffix}.int8.onnx"
+
     quantize_dynamic(
         model_input=encoder_filename,
         model_output=encoder_filename_int8,
diff --git a/egs/librispeech/ASR/zipformer/export-onnx.py b/egs/librispeech/ASR/zipformer/export-onnx.py
index a56a7a3e6..03c7d6f82 100755
--- a/egs/librispeech/ASR/zipformer/export-onnx.py
+++ b/egs/librispeech/ASR/zipformer/export-onnx.py
@@ -70,7 +70,6 @@ import onnx
 import torch
 import torch.nn as nn
 from decoder import Decoder
-from onnxconverter_common import float16
 from onnxruntime.quantization import QuantType, quantize_dynamic
 from scaling_converter import convert_scaled_to_non_scaled
 from train import add_model_arguments, get_model, get_params
@@ -182,6 +181,15 @@ def add_meta_data(filename: str, meta_data: Dict[str, str]):
     onnx.save(model, filename)
 
 
+def export_onnx_fp16(onnx_fp32_path, onnx_fp16_path):
+    import onnxmltools
+    from onnxmltools.utils.float16_converter import convert_float_to_float16
+
+    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)
+
+
 class OnnxEncoder(nn.Module):
     """A wrapper for Zipformer and the encoder_proj from the joiner"""
 
@@ -595,20 +603,14 @@ def main():
     if params.fp16:
         logging.info("Generate fp16 models")
 
-        encoder = onnx.load(encoder_filename)
-        encoder_fp16 = float16.convert_float_to_float16(encoder, keep_io_types=True)
         encoder_filename_fp16 = params.exp_dir / f"encoder-{suffix}.fp16.onnx"
-        onnx.save(encoder_fp16, encoder_filename_fp16)
+        export_onnx_fp16(encoder_filename, encoder_filename_fp16)
 
-        decoder = onnx.load(decoder_filename)
-        decoder_fp16 = float16.convert_float_to_float16(decoder, keep_io_types=True)
         decoder_filename_fp16 = params.exp_dir / f"decoder-{suffix}.fp16.onnx"
-        onnx.save(decoder_fp16, decoder_filename_fp16)
+        export_onnx_fp16(decoder_filename, decoder_filename_fp16)
 
-        joiner = onnx.load(joiner_filename)
-        joiner_fp16 = float16.convert_float_to_float16(joiner, keep_io_types=True)
         joiner_filename_fp16 = params.exp_dir / f"joiner-{suffix}.fp16.onnx"
-        onnx.save(joiner_fp16, joiner_filename_fp16)
+        export_onnx_fp16(joiner_filename, joiner_filename_fp16)
 
     # Generate int8 quantization models
     # See https://onnxruntime.ai/docs/performance/model-optimizations/quantization.html#data-type-selection