Update app.py

app.py

@@ -105,24 +105,23 @@ class App:
                 input_file_multi = gr.Files(label="Upload one or more audio/video files here", elem_id="multi_input", type='filepath', file_count="multiple", allow_reordering=True, file_types=["audio","video"], visible=False, interactive=True)                        
                     
         with gr.Row():
-            with gr.Column(scale=3):
+            with gr.Column(scale=4):
                 with gr.Row():
                     model_list = self.whisper_inf.available_models if len(whisper_params["model_list"]) == 0 else whisper_params["model_list"]
                     dd_model = gr.Dropdown(choices=model_list, value=whisper_params["model_size"],label="Model", info="Larger models increase transcription quality, but reduce performance", interactive=True)
                     dd_lang = gr.Dropdown(choices=["Automatic Detection"] + self.whisper_inf.available_langs,value=whisper_params["lang"], label="Language", info="Select the language if known upfront", interactive=True)
+                    cb_translate = gr.Checkbox(value=whisper_params["is_translate"], label="Translate to English", info="Translate using OpenAI Whisper's built-in module",interactive=True)
                 with gr.Row():
                     dd_translate_model = gr.Dropdown(choices=self.nllb_inf.available_models, value=nllb_params["model_size"],label="Model", info="Model used for translation", interactive=True)
                     dd_target_lang = gr.Dropdown(choices=["English","Dutch","French","German"], value=nllb_params["target_lang"],label="Language", info="Language used for output translation", interactive=True)
+                    cb_translate_output = gr.Checkbox(value=translation_params["translate_output"], label="Translate to selected language", info="Translate using Facebook's NLLB",interactive=True)
             with gr.Column(scale=1):
                 with gr.Row():
                     cb_timestamp_preview = gr.Checkbox(value=whisper_params["add_timestamp_preview"],label="Add timestamp to preview", interactive=True)
                     cb_timestamp_file = gr.Checkbox(value=whisper_params["add_timestamp_file"], label="Add timestamp to output", interactive=True)
                 with gr.Row():
                     cb_diarize = gr.Checkbox(value=diarization_params["is_diarize"],label="Speaker diarization", info="Token required for diarization",interactive=True)
-            with gr.Column(scale=1):
-                cb_translate = gr.Checkbox(value=whisper_params["is_translate"], label="Translate to English", info="Translate using OpenAI Whisper's built-in module",interactive=True)
-                cb_translate_output = gr.Checkbox(value=translation_params["translate_output"], label="Translate to selected language", info="Translate using Facebook's NLLB",interactive=True)
-                
+
         with gr.Accordion("Diarization options", open=False, visible=True):
             tb_hf_token = gr.Text(label="Token", value=diarization_params["hf_token"],info="An access token is required to use diarization & can be created [here](https://hf.co/settings/tokens). If not done yet for your account, you need to accept the terms & conditions of [diarization](https://huggingface.co/pyannote/speaker-diarization-3.1) & [segmentation](https://huggingface.co/pyannote/segmentation-3.0).")
             dd_diarization_device = gr.Dropdown(label="Device",