model_assets ├── your_model │ ├── config.json │ ├── your_model_file1.safetensors │ ├── your_model_file2.safetensors │ ├── ... │ └── style_vectors.npy └── another_model ├── ... このように、推論にはconfig.jsonと*.safetensorsとstyle_vectors.npyが必...
model_id: str, initial_prompt: Optional[str] = None, language: str = "ja", batch_size: int = 16, num_beams: int = 1, no_repeat_ngram_size: int = 10, device: str = "cuda", pbar: Optional[tqdm] = None, ) -> list[str]: ...
The pretrained model and JP-Extra version is essentially taken from the original base model of Bert-VITS2 v2.1 and JP-Extra pretrained model of Bert-VITS2, so all the credits go to the original author (Fish Audio): In addition, text/user_dict/ module is based on the following repositorie...
( self, device: str, model: str, config_path: str, language_identification_library: str, port: int = 7860, share: bool = False, debug: bool = False, ): if not cuda_available: device = "cpu" self.device: str = device self.model: str = model # 端口号 self.config_path: str =...
model_assets ├── your_model │ ├── config.json │ ├── your_model_file1.safetensors │ ├── your_model_file2.safetensors │ ├── ... │ └── style_vectors.npy └── another_model ├── ... このように、推論にはconfig.jsonと*.safetensorsとstyle_vectors.npyが...
model_assets ├── your_model │ ├── config.json │ ├── your_model_file1.safetensors │ ├── your_model_file2.safetensors │ ├── ... │ └── style_vectors.npy └── another_model ├── ... このように、推論にはconfig.jsonと*.safetensorsとstyle_vectors.npyが...
Style-Bert-VITS2_en.md TERMS_OF_USE.md paperspace.md gradio_tabs inputs model_assets scripts slm style_bert_vits2 tests .dockerignore .gitattributes .gitignore App.bat Dataset.bat Dockerfile.deploy Dockerfile.train Editor.bat Inference.bat Initialize.bat LGPL_LICENSE LICENSE Merge.bat README.md...
model_assets ├── your_model │ ├── config.json │ ├── your_model_file1.safetensors │ ├── your_model_file2.safetensors │ ├── ... │ └── style_vectors.npy └── another_model ├── ... このように、推論にはconfig.jsonと*.safetensorsとstyle_vectors.npyが必...
model_assets monotonic_align scripts slm text tools .dockerignore .gitattributes .gitignore App.bat Dataset.bat Dockerfile.deploy Dockerfile.train Editor.bat LGPL_LICENSE LICENSE Merge.bat README.md Style.bat Train.bat app.py attentions.py bert_gen.py clustering.ipynb colab.ipynb commons.py config...
model = Model.from_pretrained("pyannote/wespeaker-voxceleb-resnet34-LM") inference = Inference(model, window="whole") device = torch.device(config.style_gen_config.device) inference.to(device)class NaNValueError(ValueError): """カスタム例外クラス。NaN値が見つかった場合に使用されます。"""...