Rename model

app.py

@@ -196,7 +196,7 @@ class App:
         dd_model.change(fn=self.on_change_models, inputs=[dd_model], outputs=[cb_translate])
 
         return (
-            WhisperGradioComponents(
+            TranscriptionPipelineGradioComponents(
                 model_size=dd_model, lang=dd_lang, is_translate=cb_translate, beam_size=nb_beam_size,
                 log_prob_threshold=nb_log_prob_threshold, no_speech_threshold=nb_no_speech_threshold,
                 compute_type=dd_compute_type, best_of=nb_best_of, patience=nb_patience,

modules/whisper/faster_whisper_inference.py

@@ -62,7 +62,7 @@ class FasterWhisperInference(WhisperBase):
         """
         start_time = time.time()
 
-        params = WhisperGradioComponents.as_value(*whisper_params)
+        params = TranscriptionPipelineGradioComponents.as_value(*whisper_params)
 
         if params.model_size != self.current_model_size or self.model is None or self.current_compute_type != params.compute_type:
             self.update_model(params.model_size, params.compute_type, progress)

modules/whisper/insanely_fast_whisper_inference.py

@@ -61,7 +61,7 @@ class InsanelyFastWhisperInference(WhisperBase):
             elapsed time for transcription
         """
         start_time = time.time()
-        params = WhisperGradioComponents.as_value(*whisper_params)
+        params = TranscriptionPipelineGradioComponents.as_value(*whisper_params)
 
         if params.model_size != self.current_model_size or self.model is None or self.current_compute_type != params.compute_type:
             self.update_model(params.model_size, params.compute_type, progress)

modules/whisper/whisper_Inference.py

@@ -51,7 +51,7 @@ class WhisperInference(WhisperBase):
             elapsed time for transcription
         """
         start_time = time.time()
-        params = WhisperGradioComponents.as_value(*whisper_params)
+        params = TranscriptionPipelineGradioComponents.as_value(*whisper_params)
 
         if params.model_size != self.current_model_size or self.model is None or self.current_compute_type != params.compute_type:
             self.update_model(params.model_size, params.compute_type, progress)

modules/whisper/whisper_base.py

@@ -99,7 +99,7 @@ class WhisperBase(ABC):
         elapsed_time: float
             elapsed time for running
         """
-        params = WhisperGradioComponents.as_value(*whisper_params)
+        params = TranscriptionPipelineGradioComponents.as_value(*whisper_params)
 
         self.cache_parameters(
             whisper_params=params,