diff --git a/README.rst b/README.rst
index b6b347c6..60aa999b 100644
--- a/README.rst
+++ b/README.rst
@@ -36,7 +36,7 @@ To install and use deepspeech all you have to do is:
    # Transcribe an audio file
    deepspeech --model deepspeech-0.5.1-models/output_graph.pbmm --alphabet deepspeech-0.5.1-models/alphabet.txt --lm deepspeech-0.5.1-models/lm.binary --trie deepspeech-0.5.1-models/trie --audio audio/2830-3980-0043.wav
 
-A pre-trained English model is available for use and can be downloaded using `the instructions below <#using-a-pre-trained-model>`_. Currently, only 16-bit, 16 kHz, mono-channel WAVE audio files are supported in the Python client. A package with some example audio files is available for download in our `release notes <https://github.com/mozilla/DeepSpeech/releases/latest>`_.
+A pre-trained English model is available for use and can be downloaded using `the instructions below <USING.rst#using-a-pre-trained-model>`_. Currently, only 16-bit, 16 kHz, mono-channel WAVE audio files are supported in the Python client. A package with some example audio files is available for download in our `release notes <https://github.com/mozilla/DeepSpeech/releases/latest>`_.
 
 Quicker inference can be performed using a supported NVIDIA GPU on Linux. See the `release notes <https://github.com/mozilla/DeepSpeech/releases/latest>`_ to find which GPUs are supported. To run ``deepspeech`` on a GPU, install the GPU specific package:
 
@@ -52,7 +52,7 @@ Quicker inference can be performed using a supported NVIDIA GPU on Linux. See th
    # Transcribe an audio file.
    deepspeech --model deepspeech-0.5.1-models/output_graph.pbmm --alphabet deepspeech-0.5.1-models/alphabet.txt --lm deepspeech-0.5.1-models/lm.binary --trie deepspeech-0.5.1-models/trie --audio audio/2830-3980-0043.wav
 
-Please ensure you have the required `CUDA dependencies <#cuda-dependency>`_.
+Please ensure you have the required `CUDA dependencies <USING.rst#cuda-dependency>`_.
 
 See the output of ``deepspeech -h`` for more information on the use of ``deepspeech``. (If you experience problems running ``deepspeech``\ , please check `required runtime dependencies <native_client/README.md#required-dependencies>`_\ ).
 
diff --git a/TRAINING.rst b/TRAINING.rst
index 6bbdee03..c51b2079 100644
--- a/TRAINING.rst
+++ b/TRAINING.rst
@@ -66,7 +66,7 @@ If you have a capable (NVIDIA, at least 8GB of VRAM) GPU, it is highly recommend
    pip3 uninstall tensorflow
    pip3 install 'tensorflow-gpu==1.14.0'
 
-Please ensure you have the required `CUDA dependency <#cuda-dependency>`_.
+Please ensure you have the required `CUDA dependency <USING.rst#cuda-dependency>`_.
 
 It has been reported for some people failure at training:
 
@@ -75,7 +75,7 @@ It has been reported for some people failure at training:
    tensorflow.python.framework.errors_impl.UnknownError: Failed to get convolution algorithm. This is probably because cuDNN failed to initialize, so try looking to see if a warning log message was printed above.
         [[{{node tower_0/conv1d/Conv2D}}]]
 
-Setting the ``TF_FORCE_GPU_ALLOW_GROWTH`` environment variable to ``true`` seems to help in such cases. This could also be due to an incorrect version of libcudnn. Double check your versions with the `TensorFlow 1.14 documentation <#cuda-dependency>`_.
+Setting the ``TF_FORCE_GPU_ALLOW_GROWTH`` environment variable to ``true`` seems to help in such cases. This could also be due to an incorrect version of libcudnn. Double check your versions with the `TensorFlow 1.14 documentation <USING.rst#cuda-dependency>`_.
 
 Common Voice training data
 ^^^^^^^^^^^^^^^^^^^^^^^^^^