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-rw-r--r--tensorflow/docs_src/tutorials/sequences/recurrent.md2
1 files changed, 1 insertions, 1 deletions
diff --git a/tensorflow/docs_src/tutorials/sequences/recurrent.md b/tensorflow/docs_src/tutorials/sequences/recurrent.md
index 10d60f7966..39ad441381 100644
--- a/tensorflow/docs_src/tutorials/sequences/recurrent.md
+++ b/tensorflow/docs_src/tutorials/sequences/recurrent.md
@@ -138,7 +138,7 @@ for current_batch_of_words in words_in_dataset:
### Inputs
The word IDs will be embedded into a dense representation (see the
-@{$word2vec$Vector Representations Tutorial}) before feeding to
+[Vector Representations Tutorial](../../tutorials/representation/word2vec.md)) before feeding to
the LSTM. This allows the model to efficiently represent the knowledge about
particular words. It is also easy to write: