mirror of
https://github.com/FunAudioLLM/CosyVoice.git
synced 2026-02-04 09:29:25 +08:00
update vc code
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16
README.md
16
README.md
@@ -71,6 +71,7 @@ If you are expert in this field, and you are only interested in training your ow
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# SDK模型下载
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from modelscope import snapshot_download
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snapshot_download('iic/CosyVoice-300M', local_dir='pretrained_models/CosyVoice-300M')
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snapshot_download('iic/CosyVoice-300M-25Hz', local_dir='pretrained_models/CosyVoice-300M-25Hz')
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snapshot_download('iic/CosyVoice-300M-SFT', local_dir='pretrained_models/CosyVoice-300M-SFT')
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snapshot_download('iic/CosyVoice-300M-Instruct', local_dir='pretrained_models/CosyVoice-300M-Instruct')
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snapshot_download('iic/CosyVoice-ttsfrd', local_dir='pretrained_models/CosyVoice-ttsfrd')
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@@ -80,6 +81,7 @@ snapshot_download('iic/CosyVoice-ttsfrd', local_dir='pretrained_models/CosyVoice
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# git模型下载,请确保已安装git lfs
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mkdir -p pretrained_models
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git clone https://www.modelscope.cn/iic/CosyVoice-300M.git pretrained_models/CosyVoice-300M
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git clone https://www.modelscope.cn/iic/CosyVoice-300M-25Hz.git pretrained_models/CosyVoice-300M-25Hz
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git clone https://www.modelscope.cn/iic/CosyVoice-300M-SFT.git pretrained_models/CosyVoice-300M-SFT
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git clone https://www.modelscope.cn/iic/CosyVoice-300M-Instruct.git pretrained_models/CosyVoice-300M-Instruct
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git clone https://www.modelscope.cn/iic/CosyVoice-ttsfrd.git pretrained_models/CosyVoice-ttsfrd
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@@ -118,7 +120,7 @@ print(cosyvoice.list_avaliable_spks())
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for i, j in enumerate(cosyvoice.inference_sft('你好,我是通义生成式语音大模型,请问有什么可以帮您的吗?', '中文女', stream=False)):
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torchaudio.save('sft_{}.wav'.format(i), j['tts_speech'], 22050)
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cosyvoice = CosyVoice('pretrained_models/CosyVoice-300M-25Hz')
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cosyvoice = CosyVoice('pretrained_models/CosyVoice-300M-25Hz') # or change to pretrained_models/CosyVoice-300M for 50Hz inference
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# zero_shot usage, <|zh|><|en|><|jp|><|yue|><|ko|> for Chinese/English/Japanese/Cantonese/Korean
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prompt_speech_16k = load_wav('zero_shot_prompt.wav', 16000)
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for i, j in enumerate(cosyvoice.inference_zero_shot('收到好友从远方寄来的生日礼物,那份意外的惊喜与深深的祝福让我心中充满了甜蜜的快乐,笑容如花儿般绽放。', '希望你以后能够做的比我还好呦。', prompt_speech_16k, stream=False)):
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@@ -127,18 +129,16 @@ for i, j in enumerate(cosyvoice.inference_zero_shot('收到好友从远方寄来
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prompt_speech_16k = load_wav('cross_lingual_prompt.wav', 16000)
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for i, j in enumerate(cosyvoice.inference_cross_lingual('<|en|>And then later on, fully acquiring that company. So keeping management in line, interest in line with the asset that\'s coming into the family is a reason why sometimes we don\'t buy the whole thing.', prompt_speech_16k, stream=False)):
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torchaudio.save('cross_lingual_{}.wav'.format(i), j['tts_speech'], 22050)
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cosyvoice = CosyVoice('pretrained_models/CosyVoice-300M-Instruct')
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# instruct usage, support <laughter></laughter><strong></strong>[laughter][breath]
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for i, j in enumerate(cosyvoice.inference_instruct('在面对挑战时,他展现了非凡的<strong>勇气</strong>与<strong>智慧</strong>。', '中文男', 'Theo \'Crimson\', is a fiery, passionate rebel leader. Fights with fervor for justice, but struggles with impulsiveness.', stream=False)):
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torchaudio.save('instruct_{}.wav'.format(i), j['tts_speech'], 22050)
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cosyvoice = CosyVoice('pretrained_models/CosyVoice-VC')
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# vc usage
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prompt_speech_16k = load_wav('zero_shot_prompt.wav', 16000)
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source_speech_16k = load_wav('cross_lingual_prompt.wav', 16000)
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for i, j in enumerate(cosyvoice.inference_vc(source_speech_16k, prompt_speech_16k, stream=False)):
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torchaudio.save('vc_{}.wav'.format(i), j['tts_speech'], 22050)
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cosyvoice = CosyVoice('pretrained_models/CosyVoice-300M-Instruct')
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# instruct usage, support <laughter></laughter><strong></strong>[laughter][breath]
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for i, j in enumerate(cosyvoice.inference_instruct('在面对挑战时,他展现了非凡的<strong>勇气</strong>与<strong>智慧</strong>。', '中文男', 'Theo \'Crimson\', is a fiery, passionate rebel leader. Fights with fervor for justice, but struggles with impulsiveness.', stream=False)):
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torchaudio.save('instruct_{}.wav'.format(i), j['tts_speech'], 22050)
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```
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**Start web demo**
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@@ -25,7 +25,6 @@ class CosyVoice:
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def __init__(self, model_dir, load_jit=True, load_onnx=False):
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instruct = True if '-Instruct' in model_dir else False
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vc = True if '-VC' in model_dir else False
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self.model_dir = model_dir
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if not os.path.exists(model_dir):
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model_dir = snapshot_download(model_dir)
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@@ -37,7 +36,6 @@ class CosyVoice:
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'{}/speech_tokenizer_v1.onnx'.format(model_dir),
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'{}/spk2info.pt'.format(model_dir),
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instruct,
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vc,
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configs['allowed_special'])
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self.model = CosyVoiceModel(configs['llm'], configs['flow'], configs['hift'])
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self.model.load('{}/llm.pt'.format(model_dir),
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@@ -42,7 +42,6 @@ class CosyVoiceFrontEnd:
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speech_tokenizer_model: str,
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spk2info: str = '',
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instruct: bool = False,
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vc: bool = False,
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allowed_special: str = 'all'):
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self.tokenizer = get_tokenizer()
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self.feat_extractor = feat_extractor
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@@ -59,7 +58,6 @@ class CosyVoiceFrontEnd:
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else:
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self.spk2info = {}
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self.instruct = instruct
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self.vc = vc
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self.allowed_special = allowed_special
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self.inflect_parser = inflect.engine()
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self.use_ttsfrd = use_ttsfrd
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@@ -54,10 +54,9 @@ class CosyVoiceModel:
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self.hift_cache_dict = {}
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def load(self, llm_model, flow_model, hift_model):
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if self.llm is not None:
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self.llm.load_state_dict(torch.load(llm_model, map_location=self.device))
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self.llm.to(self.device).eval()
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self.llm.half()
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self.llm.load_state_dict(torch.load(llm_model, map_location=self.device))
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self.llm.to(self.device).eval()
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self.llm.half()
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self.flow.load_state_dict(torch.load(flow_model, map_location=self.device))
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self.flow.to(self.device).eval()
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self.hift.load_state_dict(torch.load(hift_model, map_location=self.device))
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