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Implement use_auth_token on load_model #1172

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Implement use_auth_token on load_model #1172

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10 changes: 7 additions & 3 deletions whisperx/asr.py
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Original file line number Diff line number Diff line change
@@ -1,6 +1,6 @@
import os
from typing import List, Optional, Union
from dataclasses import replace
from typing import List, Optional, Union

import ctranslate2
import faster_whisper
Expand All @@ -13,7 +13,7 @@

from whisperx.audio import N_SAMPLES, SAMPLE_RATE, load_audio, log_mel_spectrogram
from whisperx.types import SingleSegment, TranscriptionResult
from whisperx.vads import Vad, Silero, Pyannote
from whisperx.vads import Pyannote, Silero, Vad


def find_numeral_symbol_tokens(tokenizer):
Expand Down Expand Up @@ -313,6 +313,7 @@ def load_model(
download_root: Optional[str] = None,
local_files_only=False,
threads=4,
use_auth_token: Optional[Union[str, bool]] = None,
) -> FasterWhisperPipeline:
"""Load a Whisper model for inference.
Args:
Expand All @@ -326,6 +327,7 @@ def load_model(
download_root - The root directory to download the model to.
local_files_only - If `True`, avoid downloading the file and return the path to the local cached file if it exists.
threads - The number of cpu threads to use per worker, e.g. will be multiplied by num workers.
use_auth_token - HuggingFace authentication token or True to use the token stored by the HuggingFace config folder.
Returns:
A Whisper pipeline.
"""
Expand All @@ -339,7 +341,9 @@ def load_model(
compute_type=compute_type,
download_root=download_root,
local_files_only=local_files_only,
cpu_threads=threads)
cpu_threads=threads,
use_auth_token=use_auth_token
)
if language is not None:
tokenizer = Tokenizer(model.hf_tokenizer, model.model.is_multilingual, task=task, language=language)
else:
Expand Down