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@@ -15,12 +15,12 @@ Fine tune of my V2 model on all CommonVoice dataset, it made the voice clone bet
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  **V2 Model :**
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- Tortoise base model Fine tuned on a custom multispeaker French dataset of 120k samples (SIWIS + Common Voice + M-AILABS) on 10k step with a RTX 3090 (~= 21 hours of training), with Text LR Weight at 1
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  Result : The model can speak French much better without an English accent but the voice clone hardly works
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  **V1 Model :**
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- Tortoise base model Fine tuned on a custom multispeaker French dataset of 24k samples (SIWIS + Common Voice) on 8850 step with a RTX 3090 (~= 19 hours of training)
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  **Inference :**
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  * You can use the model by downloading the "V2_9750_gpt.pth" model and use it in the tortoise-tts optimized forks (git.ecker.tech/mrq/ai-voice-cloning | 152334H/tortoise-tts-fast)
 
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  **V2 Model :**
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+ Tortoise base model Fine tuned on a custom multispeaker French dataset of 120k samples (SIWIS + Common Voice subset + M-AILABS) on 10k step with a RTX 3090 (~= 21 hours of training), with Text LR Weight at 1
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  Result : The model can speak French much better without an English accent but the voice clone hardly works
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  **V1 Model :**
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+ Tortoise base model Fine tuned on a custom multispeaker French dataset of 24k samples (SIWIS + Common Voice subset) on 8850 step with a RTX 3090 (~= 19 hours of training)
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  **Inference :**
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  * You can use the model by downloading the "V2_9750_gpt.pth" model and use it in the tortoise-tts optimized forks (git.ecker.tech/mrq/ai-voice-cloning | 152334H/tortoise-tts-fast)