Add more doc text around distinction between various pre-trained model files

This commit is contained in:
Reuben Morais 2020-06-30 20:01:44 +02:00
parent 39696f0d67
commit d0bd1e5c8e

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@ -40,6 +40,20 @@ If you want to use the pre-trained English model for performing speech-to-text,
wget https://github.com/mozilla/DeepSpeech/releases/download/v0.7.4/deepspeech-0.7.4-models.pbmm
wget https://github.com/mozilla/DeepSpeech/releases/download/v0.7.4/deepspeech-0.7.4-models.scorer
There are several pre-trained model files available in official releases. Files ending in ``.pbmm`` are compatible with clients and language bindings built against the standard TensorFlow runtime. Usually these packages are simply called ``deepspeech``. These files are also compatible with CUDA enabled clients and language bindings. These packages are usually called ``deepspeech-gpu``. Files ending in ``.tflite`` are compatible with clients and language bindings built against the `TensorFlow Lite runtime <https://www.tensorflow.org/lite/>`_. These models are optimized for size and performance in low power devices. On desktop platforms, the compatible packages are called ``deepspeech-tflite``. On Android and Raspberry Pi, we only publish TensorFlow Lite enabled packages, and they are simply called ``deepspeech``. You can see a full list of supported platforms and which TensorFlow runtime is supported at :ref:`supported-platforms-inference`.
+--------------------+---------------------+---------------------+
| Package/Model type | .pbmm | .tflite |
+====================+=====================+=====================+
| deepspeech | Depends on platform | Depends on platform |
+--------------------+---------------------+---------------------+
| deepspeech-gpu | ✅ | ❌ |
+--------------------+---------------------+---------------------+
| deepspeech-tflite | ❌ | ✅ |
+--------------------+---------------------+---------------------+
Finally, the pre-trained model files also include files ending in ``.scorer``. These are external scorers (language models) that are used at inference time in conjunction with an acoustic model (``.pbmm`` or ``.tflite`` file) to produce transcriptions. We also provide further documentation on :ref:`the decoding process <decoder-docs>` and :ref:`how language models are generated <scorer-scripts>`.
Model compatibility
^^^^^^^^^^^^^^^^^^^