update modelscope model

README.md

@@ -40,18 +40,18 @@ If you are expert in this field, and you are only interested in training your ow
 ``` python
 # SDK模型下载
 from modelscope import snapshot_download
-snapshot_download('speech_tts/CosyVoice-300M', local_dir='pretrained_models/CosyVoice-300M')
-snapshot_download('speech_tts/CosyVoice-300M-SFT', local_dir='pretrained_models/CosyVoice-300M-SFT')
-snapshot_download('speech_tts/CosyVoice-300M-Instruct', local_dir='pretrained_models/CosyVoice-300M-Instruct')
+snapshot_download('iic/CosyVoice-300M', local_dir='pretrained_models/CosyVoice-300M')
+snapshot_download('iic/CosyVoice-300M-SFT', local_dir='pretrained_models/CosyVoice-300M-SFT')
+snapshot_download('iic/CosyVoice-300M-Instruct', local_dir='pretrained_models/CosyVoice-300M-Instruct')
 snapshot_download('speech_tts/speech_kantts_ttsfrd', local_dir='pretrained_models/speech_kantts_ttsfrd')
 ```
 
 ``` sh
 # git模型下载，请确保已安装git lfs
 mkdir -p pretrained_models
-git clone https://www.modelscope.cn/speech_tts/CosyVoice-300M.git pretrained_models/CosyVoice-300M
-git clone https://www.modelscope.cn/speech_tts/CosyVoice-300M-SFT.git pretrained_models/CosyVoice-300M-SFT
-git clone https://www.modelscope.cn/speech_tts/CosyVoice-300M-Instruct.git pretrained_models/CosyVoice-300M-Instruct
+git clone https://www.modelscope.cn/iic/CosyVoice-300M.git pretrained_models/CosyVoice-300M
+git clone https://www.modelscope.cn/iic/CosyVoice-300M-SFT.git pretrained_models/CosyVoice-300M-SFT
+git clone https://www.modelscope.cn/iic/CosyVoice-300M-Instruct.git pretrained_models/CosyVoice-300M-Instruct
 git clone https://www.modelscope.cn/speech_tts/speech_kantts_ttsfrd.git pretrained_models/speech_kantts_ttsfrd
 ```
 

cosyvoice/cli/frontend.py

@@ -42,7 +42,7 @@ class CosyVoiceFrontEnd:
         option.graph_optimization_level = onnxruntime.GraphOptimizationLevel.ORT_ENABLE_ALL
         option.intra_op_num_threads = 1
         self.campplus_session = onnxruntime.InferenceSession(campplus_model, sess_options=option, providers=["CPUExecutionProvider"])
-        self.speech_tokenizer_session = onnxruntime.InferenceSession(speech_tokenizer_model, sess_options=option, providers=["CUDAExecutionProvider", "CPUExecutionProvider"])
+        self.speech_tokenizer_session = onnxruntime.InferenceSession(speech_tokenizer_model, sess_options=option, providers=["CUDAExecutionProvider"if torch.cuda.is_available() else "CPUExecutionProvider"])
         if os.path.exists(spk2info):
             self.spk2info = torch.load(spk2info, map_location=self.device)
         self.instruct = instruct