+ TV-jf^RIHt^RIHt^RIHt^RIHtRRRRRR/tR R R llt R R R llt R#))Path)UnionN)base_load_modelsilero silero_vadz silero-vadfsmnc~V^8dQhR\\\3,R\R\R\P /# model_pathlazystrictreturnrstrrboolnnModule)formats"d/Volumes/fast/ai/experiments/ui-tars-smoke/.venv/lib/python3.14/site-packages/mlx_audio/vad/utils.py __annotate__r s9c4i (,>BYYc 4\RRVRRR\RVRV/VB#)a Load and initialize a VAD/diarization model from a given path. Args: model_path: The path or HuggingFace repo to load the model from. lazy: If False, evaluate model parameters immediately. strict: If True, raise an error if any weights are missing. **kwargs: Additional keyword arguments (revision, force_download). Returns: nn.Module: The loaded and initialized model. r categoryvadmodel_remappingr r)rMODEL_REMAPPINGr r rkwargss&&&,r load_modelr! sI    (         rc~V^8dQhR\\\3,R\R\R\P /#r r)rs"rrr$s?FFc4i F(,F>BFYYFrc "\V3RVRV/VB#)a= Load a VAD/diarization model from a local path or HuggingFace repository. This is the main entry point for loading VAD models. It automatically detects the model type and initializes the appropriate model class. Args: model_path: The local path or HuggingFace repo ID to load from. lazy: If False, evaluate model parameters immediately. strict: If True, raise an error if any weights are missing. **kwargs: Additional keyword arguments: - revision (str): HuggingFace revision/branch to use - force_download (bool): Force re-download of model files Returns: nn.Module: The loaded and initialized model. Example: >>> from mlx_audio.vad import load >>> model = load("mlx-community/diar_streaming_sortformer_4spk-v2.1-fp16") >>> result = model.generate("audio.wav", verbose=True) r r)r!rs&&&,rloadr$$s2 j Et EF Ef EEr)FF) pathlibrtypingrmlx.nnrmlx_audio.utilsrrr!r$rrrr)s4+\<vvV2FFr