Update app.py

app.py

@@ -16,11 +16,11 @@ device = "cuda" if torch.cuda.is_available() else "cpu"
 #model_checkpoint = "oza75/whisper-bambara-asr-002"
 #revision = "831cd15ed74a554caac9f304cf50dc773841ba1b"
 model_checkpoint = "oza75/whisper-bambara-asr-005"
-#revision = "6a92cd0f19985d12739c2f6864607627115e015d" # first good checkpoint for bambara
+revision = "6a92cd0f19985d12739c2f6864607627115e015d" # first good checkpoint for bambara
 #revision = "fb69a5750182933868397543366dbb63747cf40c" # this only translate in english
 #revision = "129f9e68ead6cc854e7754b737b93aa78e0e61e1" # support transcription and translation
 #revision = "cb8e351b35d6dc524066679d9646f4a947300b27"
-revision = "5f143f6070b64412a44fea08e912e1b7312e9ae9" # this checkpoint support both task without overfitting
+#revision = "5f143f6070b64412a44fea08e912e1b7312e9ae9" # this checkpoint support both task without overfitting
 
 #model_checkpoint = "oza75/whisper-bambara-asr-006"
 #revision = "96535debb4ce0b7af7c9c186d09d088825f63840"
@@ -102,7 +102,7 @@ def main():
         fn=transcribe,
         inputs=[
             gr.Audio(type="filepath", value=example_files[0][0]),
-            gr.Radio(choices=["transcribe", "translate"], label="Task Type", value="transcribe")
+            gr.Radio(choices=["transcribe"], label="Task Type", value="transcribe")
         ],
         outputs="text",
         title="Bambara Automatic Speech Recognition",