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@@ -75,7 +75,7 @@ This model powers voice interactions in the modern agentic systems, enabling sea
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  - Dataset: Curated from LibriTTS, Common Voice and Emilia (~50k hours).
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  - Pretrained mostly on English speech for robust core capabilities, with multilingual fine-tuning for supported languages.
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  - Metrics: MOS (Mean Opinion Score) 4.3/5 for naturalness; WER (Word Error Rate) < 5% on benchmark texts.
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- - Hardware: Pretrained on 8x H200 over 25 hours.
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  ## Inference on Nvidia RTX 5080:
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  - **Latency**: ~ 1s to generate 15 seconds of audio
 
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  - Dataset: Curated from LibriTTS, Common Voice and Emilia (~50k hours).
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  - Pretrained mostly on English speech for robust core capabilities, with multilingual fine-tuning for supported languages.
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  - Metrics: MOS (Mean Opinion Score) 4.3/5 for naturalness; WER (Word Error Rate) < 5% on benchmark texts.
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+ - Hardware: Pretrained on 8x H200 over 8 hours.
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  ## Inference on Nvidia RTX 5080:
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  - **Latency**: ~ 1s to generate 15 seconds of audio