ittailup commited on
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f3af758
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1 Parent(s): 8d5a618

Update app.py

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Files changed (1) hide show
  1. app.py +8 -12
app.py CHANGED
@@ -12,7 +12,7 @@ from transformers import AutoTokenizer, AutoFeatureExtractor, set_seed
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  device = "cuda:0" if torch.cuda.is_available() else "cpu"
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- repo_id = "parler-tts/parler_tts_mini_v0.1"
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  model = ParlerTTSForConditionalGeneration.from_pretrained(repo_id).to(device)
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  tokenizer = AutoTokenizer.from_pretrained(repo_id)
@@ -22,23 +22,19 @@ feature_extractor = AutoFeatureExtractor.from_pretrained(repo_id)
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  SAMPLE_RATE = feature_extractor.sampling_rate
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  SEED = 42
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- default_text = "Please surprise me and speak in whatever voice you enjoy."
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  examples = [
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  [
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- "Remember - this is only the first iteration of the model! To improve the prosody and naturalness of the speech further, we're scaling up the amount of training data by a factor of five times.",
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- "A male speaker with a low-pitched voice delivering his words at a fast pace in a small, confined space with a very clear audio and an animated tone."
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  ],
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  [
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- "'This is the best time of my life, Bartley,' she said happily.",
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- "A female speaker with a slightly low-pitched, quite monotone voice delivers her words at a slightly faster-than-average pace in a confined space with very clear audio.",
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  ],
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  [
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- "Montrose also, after having experienced still more variety of good and bad fortune, threw down his arms, and retired out of the kingdom.",
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- "A male speaker with a slightly high-pitched voice delivering his words at a slightly slow pace in a small, confined space with a touch of background noise and a quite monotone tone.",
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- ],
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- [
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- "Montrose also, after having experienced still more variety of good and bad fortune, threw down his arms, and retired out of the kingdom.",
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- "A male speaker with a low-pitched voice delivers his words at a fast pace and an animated tone, in a very spacious environment, accompanied by noticeable background noise.",
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  ],
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  ]
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  device = "cuda:0" if torch.cuda.is_available() else "cpu"
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+ repo_id = "ittailup/pe-v0.1"
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  model = ParlerTTSForConditionalGeneration.from_pretrained(repo_id).to(device)
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  tokenizer = AutoTokenizer.from_pretrained(repo_id)
 
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  SAMPLE_RATE = feature_extractor.sampling_rate
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  SEED = 42
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+ default_text = "Estos pendientes que me los he puesto hoy dia, ¿saben que marca es?"
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  examples = [
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  [
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+ "oficial sobre acciones ya consumadas, no? Entonces aquí quisiera simplemente dejar.",
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+ "A man from Peru delivers a speech in a moderately reverberant room with a quiet hum of ambient sound, speaking in a monotone tone at a slightly slow pace, with a slightly low-pitched voice."
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  ],
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  [
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+ "No será, como decan estos congresistas, porque donde no hay coima, los funcionarios locales no ponen energa?",
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+ "A man from Peru delivers a speech in a quite low-pitched, slightly slow, and quite monotone tone in a space that sounds quite confined, with a very good recording quality.",
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  ],
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  [
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+ "que solo el cuarenta por ciento de familias tiene Internet en casa, sesenta por ciento no lo tiene, por tanto estaban fuera del conteo",
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+ "A female speaker from Peru delivers her speech in a slightly muffled and confined space with a hint of background noise. Her voice has a high pitch and remains fairly monotone, with a moderate speed of delivery.",
 
 
 
 
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  ],
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  ]
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