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Minor fixes
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@ -145,7 +145,7 @@ def get_parser():
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"--tokens",
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type=str,
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default="data/lang_bpe_500/tokens.txt",
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help="Path to the BPE model",
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help="Path to the tokens.txt",
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)
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parser.add_argument(
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@ -22,29 +22,29 @@
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This script loads ONNX exported models and uses them to decode the test sets.
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We use the pre-trained model from
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https://huggingface.co/csukuangfj/icefall-asr-librispeech-pruned-transducer-stateless7-2022-11-11
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https://huggingface.co/pkufool/icefall-asr-zipformer-wenetspeech-20230615
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as an example to show how to use this file.
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1. Download the pre-trained model
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cd egs/librispeech/ASR
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cd egs/wenetspeech/ASR
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repo_url=https://huggingface.co/csukuangfj/icefall-asr-librispeech-pruned-transducer-stateless7-2022-11-11
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repo_url=https://huggingface.co/pkufool/icefall-asr-zipformer-wenetspeech-20230615
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GIT_LFS_SKIP_SMUDGE=1 git clone $repo_url
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repo=$(basename $repo_url)
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pushd $repo
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git lfs pull --include "data/lang_bpe_500/bpe.model"
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git lfs pull --include "exp/pretrained-epoch-30-avg-9.pt"
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git lfs pull --include "data/lang_char/tokens.txt"
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git lfs pull --include "exp/pretrained.pt"
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cd exp
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ln -s pretrained-epoch-30-avg-9.pt epoch-9999.pt
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ln -s pretrained.pt epoch-9999.pt
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popd
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2. Export the model to ONNX
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./pruned_transducer_stateless7/export-onnx.py \
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--bpe-model $repo/data/lang_bpe_500/bpe.model \
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./zipformer/export-onnx.py \
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--tokens $repo/data/lang_char/tokens.txt \
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--epoch 9999 \
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--avg 1 \
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--exp-dir $repo/exp/
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@ -57,8 +57,8 @@ It will generate the following 3 files inside $repo/exp:
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2. Run this file
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./pruned_transducer_stateless7/onnx_decode.py \
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--exp-dir ./pruned_transducer_stateless7/exp \
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./zipformer/onnx_decode.py \
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--exp-dir ./zipformer/exp \
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--max-duration 600 \
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--encoder-model-filename $repo/exp/encoder-epoch-9999-avg-1.onnx \
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--decoder-model-filename $repo/exp/decoder-epoch-9999-avg-1.onnx \
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