DataLossError (see above for traceback): Unable to open table file /wmt16_systems/en-de/model.npz: Data loss: not an sstable

Hi, I am trying to use pretrained model en-de from (http://data.statmt.org/rsennrich/wmt16_systems/ ) and translate english sentence with this script:

# this sample script translates a test set, including
# preprocessing (tokenization, truecasing, and subword segmentation),
# and postprocessing (merging subword units, detruecasing, detokenization).

# instructions: set paths to mosesdecoder, subword_nmt, and nematus,
# then run "./translate.sh < input_file > output_file"

# suffix of source language
SRC=en

# suffix of target language
TRG=de

# path to moses decoder: https://github.com/moses-smt/mosesdecoder
mosesdecoder=../../mosesdecoder

# path to subword segmentation scripts: https://github.com/rsennrich/subword-nmt
subword_nmt=../../subword-nmt

# path to nematus ( https://www.github.com/rsennrich/nematus )
nematus=../../nematus

# theano device
device=cpu

# preprocess
$mosesdecoder/scripts/tokenizer/normalize-punctuation.perl -l $SRC | \
$mosesdecoder/scripts/tokenizer/tokenizer.perl -l $SRC -penn | \
$mosesdecoder/scripts/recaser/truecase.perl -model truecase-model.$SRC | \
$subword_nmt/apply_bpe.py -c $SRC$TRG.bpe | \
# translate
THEANO_FLAGS=mode=FAST_RUN,floatX=float32,device=$device,on_unused_input=warn python $nematus/nematus/translate.py \
     -m model.npz \
     -k 12 -n 
#-n -p 1 --suppress-unk | \
# postprocess
sed 's/\@\@ //g' | \
$mosesdecoder/scripts/recaser/detruecase.perl | \
$mosesdecoder/scripts/tokenizer/detokenizer.perl -l $TRG

When I execute ./translate.sh < en_text.txt > output.txt, I got this error:

DataLossError (see above for traceback): Unable to open table file /wmt16_systems/en-de/model.npz: Data loss: not an sstable (bad magic number): perhaps your file is in a different file format and you need to use a different restore operator?
	 [[{{node model0/save/RestoreV2}} = RestoreV2[dtypes=[DT_FLOAT, DT_FLOAT, DT_FLOAT, DT_FLOAT, DT_FLOAT, ..., DT_FLOAT, DT_FLOAT, DT_FLOAT, DT_FLOAT, DT_FLOAT], _device="/job:localhost/replica:0/task:0/device:CPU:0"](_arg_model0/save/Const_0_0, model0/save/RestoreV2/tensor_names, model0/save/RestoreV2/shape_and_slices)]]

ERROR: Translate worker process 600 crashed with exitcode 1
Warning: No built-in rules for language de.
Detokenizer Version $Revision: 4134 $
Language: de

Could you give me any suggest? Thanks

[rsennrich]

Yes, these instructions should help you train your own model. You may want to change some things, e.g. the preprocessing, depending on the language pair.

[rsennrich]

1. This should work with all 11 language pairs on http://data.statmt.org/wmt17_systems/

2. each directory has the script postprocess.sh, which performs the necessary post-processing. For example, check http://data.statmt.org/wmt17_systems/de-en/postprocess.sh