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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Name	Size	Updated	Actions
tacotron2.yaml	4.78 KB	February 28, 2025 UTC	curl wget Download
Tacotron2Decoder.pt	69.64 MB	February 28, 2025 UTC	curl wget Download
Tacotron2Encoder.pt	21.05 MB	February 28, 2025 UTC	curl wget Download
Tacotron2Postnet.pt	16.61 MB	February 28, 2025 UTC	curl wget Download
TextEmbedding.pt	138.45 KB	February 28, 2025 UTC	curl wget Download