Update app.py

app.py

@@ -48,10 +48,10 @@ HEADER_INFO = """
     # WEB APP ✨| Norwegian WHISPER Model
 Switch Work [Transkribering av lydfiler til norsk skrift]
 """.strip()
-LOGO = "https://huggingface.co/spaces/camparchimedes/ola_s-audioshop/blob/main/pic09w9678yhit.png"
+LOGO = "https://huggingface.co/spaces/camparchimedes/transcription_app/resolve/main/pic09w9678yhit.png"
 SIDEBAR_INFO = f"""
 <div align=center>
-<img src="{LOGO}" width=100/>"""
+<img src="{LOGO}" style="width: 100%; height: auto;"/>"""
 
 warnings.filterwarnings("ignore")
 
@@ -78,13 +78,16 @@ pipe = pipeline(
     device=device,
 )
 
-def transcribe_audio(audio_file, batch_size=4):
+def transcribe_audio(audio_file, batch_size=16):
     if audio_file.endswith(".m4a"):
         audio_file = convert_to_wav(audio_file)
 
     start_time = time.time()
 
-    outputs = pipe(audio_file, batch_size=batch_size, return_timestamps=False, generate_kwargs={'num_beams': 5, 'task': 'transcribe', 'language': 'no'}) # skip_special_tokens=True
+    outputs = pipe(audio_file, batch_size=batch_size, return_timestamps=False, generate_kwargs={'task': 'transcribe', 'language': 'no'}) # skip_special_tokens=True
+    #options = dict(language=selected_source_lang, beam_size=3, best_of=3)
+    #transcribe_options = dict(task="transcribe", **options)
+    #result = model.transcribe(file, **transcribe_options)
     text = outputs["text"]
 
     end_time = time.time()