Change model to turbo

app.py

@@ -14,18 +14,19 @@ from dotenv import load_dotenv
 
 load_dotenv()
 
-MODEL_NAME = "openai/whisper-large-v3"
+MODEL_NAME = "openai/whisper-large-v3-turbo"
 BATCH_SIZE = 8
-FILE_LIMIT_MB = 1000
-YT_LENGTH_LIMIT_S = 3600  # limit to 1 hour YouTube files
+FILE_LIMIT_MB = 5000     # 5GB
+YT_LENGTH_LIMIT_S = 7200 # 2 hours
 
 device = 0 if torch.cuda.is_available() else "cpu"
 
 pipe = pipeline(
     task="automatic-speech-recognition",
     model=MODEL_NAME,
-    chunk_length_s=30,
     device=device,
+    ignore_warning=True,
+    model_kwargs={"torch_dtype": torch.float16} if torch.cuda.is_available() else {}
 )
 
 
@@ -110,9 +111,7 @@ mf_transcribe = gr.Interface(
     outputs=[gr.Textbox(label="Transcription"), gr.Textbox(label="Summary")],
     title="Whisper Large V3: Microphone",
     description=(
-        "Transcribe long-form microphone or audio inputs with the click of a button! Demo uses the"
-        f" checkpoint [{MODEL_NAME}](https://huggingface.co/{MODEL_NAME}) and 🤗 Transformers to transcribe audio files"
-        " of arbitrary length."
+        "Transcribe long-form microphone or audio inputs."
     ),
     allow_flagging="never",
 )