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feat: add local_files_only option on whisperx.load_model for offline mode (#867)

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Adds the parameter local_files_only (default False for consistency) to whisperx.load_model so that the user can avoid downloading the file and return the path to the local cached file if it exists.

---------

Co-authored-by: Barabazs <31799121+Barabazs@users.noreply.github.com>
This commit is contained in:
Roque Giordano
2025-01-01 09:16:45 -03:00
committed by GitHub
parent 51da22771f
commit 0fdb55d317
1 changed files with 3 additions and 0 deletions
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3
whisperx/asr.py
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@ -269,6 +269,7 @@ def load_model(whisper_arch,
model : Optional[WhisperModel] = None, model : Optional[WhisperModel] = None,
task="transcribe", task="transcribe",
download_root=None, download_root=None,
local_files_only=False,
threads=4): threads=4):
'''Load a Whisper model for inference. '''Load a Whisper model for inference.
Args: Args:
@ -279,6 +280,7 @@ def load_model(whisper_arch,
language: str - The language of the model. (use English for now) language: str - The language of the model. (use English for now)
model: Optional[WhisperModel] - The WhisperModel instance to use. model: Optional[WhisperModel] - The WhisperModel instance to use.
download_root: Optional[str] - The root directory to download the model to. download_root: Optional[str] - The root directory to download the model to.
local_files_only: bool - If `True`, avoid downloading the file and return the path to the local cached file if it exists.
threads: int - The number of cpu threads to use per worker, e.g. will be multiplied by num workers. threads: int - The number of cpu threads to use per worker, e.g. will be multiplied by num workers.
Returns: Returns:
A Whisper pipeline. A Whisper pipeline.
@ -292,6 +294,7 @@ def load_model(whisper_arch,
device_index=device_index, device_index=device_index,
compute_type=compute_type, compute_type=compute_type,
download_root=download_root, download_root=download_root,
local_files_only=local_files_only,
cpu_threads=threads) cpu_threads=threads)
if language is not None: if language is not None:
tokenizer = faster_whisper.tokenizer.Tokenizer(model.hf_tokenizer, model.model.is_multilingual, task=task, language=language) tokenizer = faster_whisper.tokenizer.Tokenizer(model.hf_tokenizer, model.model.is_multilingual, task=task, language=language)