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doc updated (#1214)

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zr_jin 2023-08-13 12:37:08 +08:00 committed by GitHub
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4
docs/source/model-export/export-model-state-dict.rst
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@ -41,7 +41,7 @@ as an example.
./pruned_transducer_stateless3/export.py \
--exp-dir ./pruned_transducer_stateless3/exp \
--bpe-model data/lang_bpe_500/bpe.model \
--tokens data/lang_bpe_500/tokens.txt \
--epoch 20 \
--avg 10
@ -78,7 +78,7 @@ In each recipe, there is also a file ``pretrained.py``, which can use
./pruned_transducer_stateless3/pretrained.py \
--checkpoint ./icefall-asr-librispeech-pruned-transducer-stateless3-2022-05-13/exp/pretrained-iter-1224000-avg-14.pt \
--bpe-model ./icefall-asr-librispeech-pruned-transducer-stateless3-2022-05-13/data/lang_bpe_500/bpe.model \
--tokens ./icefall-asr-librispeech-pruned-transducer-stateless3-2022-05-13/data/lang_bpe_500/tokens.txt \
--method greedy_search \
./icefall-asr-librispeech-pruned-transducer-stateless3-2022-05-13/test_wavs/1089-134686-0001.wav \
./icefall-asr-librispeech-pruned-transducer-stateless3-2022-05-13/test_wavs/1221-135766-0001.wav \

3
docs/source/model-export/export-ncnn-conv-emformer.rst
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@ -153,11 +153,10 @@ Next, we use the following code to export our model:
./conv_emformer_transducer_stateless2/export-for-ncnn.py \
--exp-dir $dir/exp \
--bpe-model $dir/data/lang_bpe_500/bpe.model \
--tokens $dir/data/lang_bpe_500/tokens.txt \
--epoch 30 \
--avg 1 \
--use-averaged-model 0 \
\
--num-encoder-layers 12 \
--chunk-length 32 \
--cnn-module-kernel 31 \

2
docs/source/model-export/export-ncnn-lstm.rst
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@ -73,7 +73,7 @@ Next, we use the following code to export our model:
./lstm_transducer_stateless2/export-for-ncnn.py \
--exp-dir $dir/exp \
--bpe-model $dir/data/lang_bpe_500/bpe.model \
--tokens $dir/data/lang_bpe_500/tokens.txt \
--epoch 99 \
--avg 1 \
--use-averaged-model 0 \

3
docs/source/model-export/export-ncnn-zipformer.rst
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@ -72,12 +72,11 @@ Next, we use the following code to export our model:
dir=./icefall-asr-librispeech-pruned-transducer-stateless7-streaming-2022-12-29
./pruned_transducer_stateless7_streaming/export-for-ncnn.py \
--bpe-model $dir/data/lang_bpe_500/bpe.model \
--tokens $dir/data/lang_bpe_500/tokens.txt \
--exp-dir $dir/exp \
--use-averaged-model 0 \
--epoch 99 \
--avg 1 \
\
--decode-chunk-len 32 \
--num-left-chunks 4 \
--num-encoder-layers "2,4,3,2,4" \

2
docs/source/model-export/export-onnx.rst
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@ -71,7 +71,7 @@ Export the model to ONNX
.. code-block:: bash
./pruned_transducer_stateless7_streaming/export-onnx.py \
--bpe-model $repo/data/lang_bpe_500/bpe.model \
--tokens $repo/data/lang_bpe_500/tokens.txt \
--use-averaged-model 0 \
--epoch 99 \
--avg 1 \

2
docs/source/model-export/export-with-torch-jit-script.rst
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@ -32,7 +32,7 @@ as an example in the following.
./pruned_transducer_stateless3/export.py \
--exp-dir ./pruned_transducer_stateless3/exp \
--bpe-model data/lang_bpe_500/bpe.model \
--tokens data/lang_bpe_500/tokens.txt \
--epoch $epoch \
--avg $avg \
--jit 1

2
docs/source/model-export/export-with-torch-jit-trace.rst
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@ -33,7 +33,7 @@ as an example in the following.
./lstm_transducer_stateless2/export.py \
--exp-dir ./lstm_transducer_stateless2/exp \
--bpe-model data/lang_bpe_500/bpe.model \
--tokens data/lang_bpe_500/tokens.txt \
--iter $iter \
--avg $avg \
--jit-trace 1