diff --git a/README.md b/README.md
index d370c60..5300707 100755
--- a/README.md
+++ b/README.md
@@ -6,8 +6,7 @@ Wavenet On Mel Spectrogram Predictions](https://arxiv.org/pdf/1712.05884.pdf).
 This implementation includes **distributed** and **fp16** support
 and uses the [LJSpeech dataset](https://keithito.com/LJ-Speech-Dataset/).
 
-Distributed and FP16 support relies on work by Christian Sarofeen and NVIDIA's
-[Apex Library](https://github.com/nvidia/apex).
+Distributed and FP16 support uses NVIDIA's [Apex] and [AMP].
 
 Visit our [website] for audio samples using our published [Tacotron 2] and
 [WaveGlow] models.
@@ -26,7 +25,8 @@ Visit our [website] for audio samples using our published [Tacotron 2] and
 5. Update .wav paths: `sed -i -- 's,DUMMY,ljs_dataset_folder/wavs,g' filelists/*.txt`
     - Alternatively, set `load_mel_from_disk=True` in `hparams.py` and update mel-spectrogram paths 
 6. Install [PyTorch 1.0]
-7. Install python requirements or build docker image 
+7. Install [Apex]
+8. Install python requirements or build docker image 
     - Install python requirements: `pip install -r requirements.txt`
 
 ## Training
@@ -77,3 +77,5 @@ Wang and Zongheng Yang.
 [pytorch 1.0]: https://github.com/pytorch/pytorch#installation
 [website]: https://nv-adlr.github.io/WaveGlow
 [ignored]: https://github.com/NVIDIA/tacotron2/blob/master/hparams.py#L22
+[Apex]: https://github.com/nvidia/apex
+[AMP]: https://github.com/NVIDIA/apex/tree/master/apex/amp
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