Overview

This is a checkpoint for the Tacotron 2 model that was trained in NeMo on LJspeech for 1200 epochs.\nIt was trained with Apex/Amp optimization level O0, with 8 * 16GB V100, and with a batch size of 48 per GPU for a total batch size of 384.

It contains the checkpoints for the Tacotron 2 Neural Modules and the yaml config file:

TextEmbedding.pt
Tacotron2Encoder.pt
Tacotron2Decoder.pt
Tacotron2Postnet.pt
tacotron2.yaml

Documentation

Refer to documentation at https://github.com/NVIDIA/NeMo

Usage example: Put the checkpoints into the checkpoint dir, and run tts_infer.py (from NeMo's TTS examples).

python tts_infer.py --model_config=$checkpoint_dir/tacotron2.yaml --eval_dataset=test.json --load_dir=$checkpoint_dir

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users logged in across NVIDIA domains.","api.ngc.nvidia.com","This cookie is managed by AWS and is used for load balancing.","bm_so","This cookie name is used to load the site as quickly as possible and to recognize bots using Akamai.","The __cf_bm cookie is a cookie necessary to support Cloudflare Bot Management, currently in private beta. 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