o pip@sddlmZddlmZddlmZddlmZddlm Z GdddeZ    dd e d e e Bd e dBd e dBd e eBdBde e BdBde dBfddZ dS))Enum)Path)hf_hub_download)HfHubHTTPError) __version__c@s&eZdZdZdZdZdefddZdS) AssetFileNamezcalibration.safetensorszpytorch_model.binz config.yamlreturncCs|jS)N)value)selfr O/home/ubuntu/.local/lib/python3.10/site-packages/pyannote/audio/utils/hf_hub.py__str__(szAssetFileName.__str__N)__name__ __module__ __qualname__ CalibrationModelPipelinestrr r r r r r#s rNmodel_id asset_file subfolderrevision cache_dirtokenrcCst|tr |ds d}zt|t|tr|jn||d|dt||d WStyKt|tr1|jn|}t d|d|d|d |d |d |d w) aDownload file from Huggingface Hub Parameters ---------- model_id : str Model identifier from the hf.co model hub. asset_file : AssetFileName Type of asset file to download. subfolder : str, optional Folder inside the model repo. revision : str, optional Revision when loading from the huggingface.co model hub. token : str or bool, optional Huggingface token to be used for downloading from Huggingface hub. cache_dir: Path or str, optional Path to the folder where files downloaded from Huggingface hub are stored. See also -------- `huggingface_hub.hf_hub_download` hf_Nmodelpyannote)r repo_typer library_namelibrary_versionrrz Could not download z from zQ. It might be because the repository is private or gated: * visit https://hf.co/zn to accept user conditions * visit https://hf.co/settings/tokens to create an authentication token * load the z$ with the `token` argument: >>> z.from_pretrained('z', token='hf_....') ) isinstancer startswithrrr rrnameprint)rrrrrrasset_file_namer r r download_from_hf_hub,sB   r&)NNNN)enumrpathlibrhuggingface_hubrhuggingface_hub.utilsrpyannote.audiorrrboolr&r r r r s2