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Merge pull request #39 from jhj0517/set-default-beam-size
Browse files
modules/faster_whisper_inference.py
CHANGED
@@ -24,7 +24,7 @@ class FasterWhisperInference(BaseInterface):
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self.available_models = whisper.available_models()
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self.available_langs = sorted(list(whisper.tokenizer.LANGUAGES.values()))
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self.translatable_models = ["large", "large-v1", "large-v2"]
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-
self.default_beam_size =
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self.device = "cuda" if torch.cuda.is_available() else "cpu"
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def transcribe_file(self,
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self.available_models = whisper.available_models()
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self.available_langs = sorted(list(whisper.tokenizer.LANGUAGES.values()))
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self.translatable_models = ["large", "large-v1", "large-v2"]
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+
self.default_beam_size = 1
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self.device = "cuda" if torch.cuda.is_available() else "cpu"
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def transcribe_file(self,
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modules/whisper_Inference.py
CHANGED
@@ -21,6 +21,7 @@ class WhisperInference(BaseInterface):
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self.model = None
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self.available_models = whisper.available_models()
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self.available_langs = sorted(list(whisper.tokenizer.LANGUAGES.values()))
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def transcribe_file(self,
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fileobjs: list,
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@@ -250,6 +251,7 @@ class WhisperInference(BaseInterface):
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segments_result = self.model.transcribe(audio=audio,
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language=lang,
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verbose=False,
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task="translate" if istranslate and self.current_model_size in translatable_model else "transcribe",
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progress_callback=progress_callback)["segments"]
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elapsed_time = time.time() - start_time
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self.model = None
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self.available_models = whisper.available_models()
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self.available_langs = sorted(list(whisper.tokenizer.LANGUAGES.values()))
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+
self.default_beam_size = 1
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def transcribe_file(self,
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fileobjs: list,
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segments_result = self.model.transcribe(audio=audio,
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language=lang,
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verbose=False,
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+
beam_size=self.default_beam_size,
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task="translate" if istranslate and self.current_model_size in translatable_model else "transcribe",
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progress_callback=progress_callback)["segments"]
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elapsed_time = time.time() - start_time
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