:jpddlmZddlmZddlmZddlmZddlm Z GddeZ dd e d e e zd e dzd e dzd e ezdzde e zdzde dzfdZ y))Enum)Path)hf_hub_download)HfHubHTTPError) __version__c$eZdZdZdZdZdefdZy) AssetFileNamezcalibration.safetensorszpytorch_model.binz config.yamlreturnc|jS)N)value)selfs p/home/mcse/projects/srt_converter/srt-converter-venv/lib/python3.12/site-packages/pyannote/audio/utils/hf_hub.py__str__zAssetFileName.__str__(s zzN)__name__ __module__ __qualname__ CalibrationModelPipelinestrrrrr r #s+K EHrr Nmodel_id asset_file subfolderrevision cache_dirtokenr cFt|tr|jdsd} t|t|tr |j n||d|dt || S#t$r>t|tr |jn|}td|d|d|d |d |d |d wxYw) 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 startswithrr r rrnameprint)rrrrrrasset_file_names rdownload_from_hf_hubr+,s@%e&6&6u&=  *:} EJ  :#'    2r2s0+0& D!#'# <<#<Tz<Dj < TzD < #:  < 4Z<r