forked from mrq/ai-voice-cloning
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@ -2068,7 +2068,7 @@ def setup_args():
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parser.add_argument("--prune-nonfinal-outputs", default=default_arguments['prune-nonfinal-outputs'], action='store_true', help="Deletes non-final output files on completing a generation")
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parser.add_argument("--device-override", default=default_arguments['device-override'], help="A device string to override pass through Torch")
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parser.add_argument("--sample-batch-size", default=default_arguments['sample-batch-size'], type=int, help="Sets how many batches to use during the autoregressive samples pass")
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parser.add_argument("--unsqueeze_sample_batches", default=default_arguments['unsqueeze_sample_batches'], action='store_true', help="Unsqueezes sample batches to process one by one after sampling")
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parser.add_argument("--unsqueeze-sample-batches", default=default_arguments['unsqueeze-sample-batches'], action='store_true', help="Unsqueezes sample batches to process one by one after sampling")
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parser.add_argument("--concurrency-count", type=int, default=default_arguments['concurrency-count'], help="How many Gradio events to process at once")
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parser.add_argument("--autocalculate-voice-chunk-duration-size", type=float, default=default_arguments['autocalculate-voice-chunk-duration-size'], help="Number of seconds to suggest voice chunk size for (for example, 100 seconds of audio at 10 seconds per chunk will suggest 10 chunks)")
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parser.add_argument("--output-sample-rate", type=int, default=default_arguments['output-sample-rate'], help="Sample rate to resample the output to (from 24KHz)")
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