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Update README.md

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  1. README.md +2 -3
README.md CHANGED
@@ -28,9 +28,8 @@ Authors: Yifan Yang, Bing Han, Hui Wang, Wei Wang, Ziyang Ma, Long Zhou, Zengrui
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  import torch
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  from transformers import AutoModel
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-
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  model = AutoModel.from_pretrained(
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- "yfyeung/CLSP",
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  trust_remote_code=True,
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  )
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  if torch.cuda.is_available():
@@ -44,7 +43,7 @@ text = [
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  "A male speaker with a medium-pitched British accent.",
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  "A female speaker delivers her enunciated words rapidly in a medium-pitched British accent, conveying an authoritative tone.",
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  "A female speaker delivers her enunciated words slowly in a medium-pitched Chinese accent, conveying an authoritative tone.",
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- "A mature female with a clear, medium-pitched voice and a British accent speaks in a formal, presentational style, characteristic of a newsreader or broadcaster. She delivers her speech at a fast pace with deliberate enunciation and a measured, authoritative rhythm. Her tone remains neutral and informative, with subtle emphasis on specific phrases, and her volume is consistently loud and steady. The delivery is fluent and controlled."
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  ]
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  with torch.no_grad():
 
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  import torch
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  from transformers import AutoModel
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  model = AutoModel.from_pretrained(
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+ "yfyeung/CLSP",
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  trust_remote_code=True,
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  )
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  if torch.cuda.is_available():
 
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  "A male speaker with a medium-pitched British accent.",
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  "A female speaker delivers her enunciated words rapidly in a medium-pitched British accent, conveying an authoritative tone.",
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  "A female speaker delivers her enunciated words slowly in a medium-pitched Chinese accent, conveying an authoritative tone.",
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+ "A mature female with a clear, medium-pitched voice and a British accent speaks in a formal, presentational style, characteristic of a newsreader or broadcaster. She delivers her speech at a fast pace with deliberate enunciation and a measured, authoritative rhythm. Her tone remains neutral and informative, with subtle emphasis on specific phrases, and her volume is consistently loud and steady. The delivery is fluent and controlled.",
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  ]
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  with torch.no_grad():