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Update README.md

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@@ -27,14 +27,18 @@ import torch
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  from parler_tts import ParlerTTSForConditionalGeneration
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  from transformers import AutoTokenizer
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  import soundfile as sf
 
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  device = "cuda:0" if torch.cuda.is_available() else "cpu"
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  model = ParlerTTSForConditionalGeneration.from_pretrained("atlithor/RepeaTTS-level-3").to(device)
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  tokenizer = AutoTokenizer.from_pretrained("atlithor/EmotiveIcelandic")
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  description_tokenizer = AutoTokenizer.from_pretrained(model.config.text_encoder._name_or_path)
 
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  prompt = "Þetta er frábær hugmynd!" # E: this is a great idea!
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  description = "The recording is of very high quality, with Ingrid's voice sounding clear and very close up. Ingrid speaks at very high intensity."
 
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  input_ids = description_tokenizer(description, return_tensors="pt").input_ids.to(device)
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  prompt_input_ids = tokenizer(prompt, return_tensors="pt").input_ids.to(device)
 
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  generation = model.generate(input_ids=input_ids, prompt_input_ids=prompt_input_ids)
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  audio_arr = generation.cpu().numpy().squeeze()
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  sf.write("ingrid_intense.wav", audio_arr, model.config.sampling_rate)
 
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  from parler_tts import ParlerTTSForConditionalGeneration
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  from transformers import AutoTokenizer
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  import soundfile as sf
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+
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  device = "cuda:0" if torch.cuda.is_available() else "cpu"
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  model = ParlerTTSForConditionalGeneration.from_pretrained("atlithor/RepeaTTS-level-3").to(device)
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  tokenizer = AutoTokenizer.from_pretrained("atlithor/EmotiveIcelandic")
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  description_tokenizer = AutoTokenizer.from_pretrained(model.config.text_encoder._name_or_path)
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+
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  prompt = "Þetta er frábær hugmynd!" # E: this is a great idea!
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  description = "The recording is of very high quality, with Ingrid's voice sounding clear and very close up. Ingrid speaks at very high intensity."
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+
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  input_ids = description_tokenizer(description, return_tensors="pt").input_ids.to(device)
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  prompt_input_ids = tokenizer(prompt, return_tensors="pt").input_ids.to(device)
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+
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  generation = model.generate(input_ids=input_ids, prompt_input_ids=prompt_input_ids)
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  audio_arr = generation.cpu().numpy().squeeze()
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  sf.write("ingrid_intense.wav", audio_arr, model.config.sampling_rate)