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Fix bogus cross-file links

This commit is contained in:
Alexandre Lissy 2019-10-08 06:46:52 +02:00
parent fb611efd00
commit 3dae00b4ab
2 changed files with 4 additions and 4 deletions
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4
README.rst
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@ -36,7 +36,7 @@ To install and use deepspeech all you have to do is:
# Transcribe an audio file # 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 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: 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. # 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 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>`_\ ). 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>`_\ ).

4
TRAINING.rst
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@ -66,7 +66,7 @@ If you have a capable (NVIDIA, at least 8GB of VRAM) GPU, it is highly recommend
pip3 uninstall tensorflow pip3 uninstall tensorflow
pip3 install 'tensorflow-gpu==1.14.0' 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: 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. 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}}]] [[{{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 Common Voice training data
^^^^^^^^^^^^^^^^^^^^^^^^^^ ^^^^^^^^^^^^^^^^^^^^^^^^^^