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merged 3 commits into from
May 10, 2022
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Modify README of bert example #174

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ae9d0a2
Modify README of bert example
chenmoneygithub May 9, 2022
6efd5b1
fix some comments
chenmoneygithub May 10, 2022
d836c28
fix some comments
chenmoneygithub May 10, 2022
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13 changes: 9 additions & 4 deletions examples/bert/README.md
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Original file line number Diff line number Diff line change
Expand Up @@ -79,7 +79,7 @@ The latest wikipedia dump can be downloaded [at this link](https://dumps.wikimed
or via command line:

```shell
curl https://dumps.wikimedia.org/enwiki/latest/enwiki-latest-pages-articles.xml.bz2
curl -O https://dumps.wikimedia.org/enwiki/latest/enwiki-latest-pages-articles.xml.bz2
```
The dump can be extracted with the `wikiextractor` tool.

Expand Down Expand Up @@ -126,7 +126,12 @@ The `create_vocabulary.py` script allows you to compute your own WordPiece
vocabulary for use with BERT. In most cases however, it is desirable to use the
standard BERT vocabularies from the original models. You can download the
English uncased vocabulary
[here](https://storage.googleapis.com/tensorflow/keras-nlp/examples/bert/bert_vocab_uncased.txt).
[here](https://storage.googleapis.com/tensorflow/keras-nlp/examples/bert/bert_vocab_uncased.txt),
or in your terminal run:

```shell
curl -O https://storage.googleapis.com/tensorflow/keras-nlp/examples/bert/bert_vocab_uncased.txt
```

### Tokenize, mask, and combine sentences into training examples

Expand Down Expand Up @@ -169,7 +174,7 @@ for file in path/to/sentence-split-data/*; do
output="path/to/pretraining-data/$(basename -- "$file" .txt).tfrecord"
python examples/bert/create_pretraining_data.py \
--input_files ${file} \
--vocab_file vocab.txt \
--vocab_file bert_vocab_uncased.txt \
--output_file ${output}
done
```
Expand All @@ -183,7 +188,7 @@ for file in path/to/sentence-split-data/*; do
output="path/to/pretraining-data/$(basename -- "$file" .txt).tfrecord"
echo python examples/bert/create_pretraining_data.py \
--input_files ${file} \
--vocab_file vocab.txt \
--vocab_file bert_vocab_uncased.txt \
--output_file ${output}
done | parallel -j ${NUM_JOBS}
```
Expand Down