Update app.py

app.py

@@ -25,6 +25,15 @@ def predict_and_ctc_lm_decode(input_file):
     sentiment = pipe1(transcribed_text)[0]["label"]
     return sentiment
 
+description = """ This is a Gradio demo for Sentiment Analysis of Transcribed Spanish Audio. First, we do Speech to Text, and then we perform sentiment analysis on the obtained transcription of the input audio. 
+
+Pre-trained model used for Spanish ASR: [jonatasgrosman/wav2vec2-xls-r-1b-spanish](https://huggingface.co/jonatasgrosman/wav2vec2-xls-r-1b-spanish)
+
+
+Pre-trained model used for Sentiment Analysis of transcribed audio: [finiteautomata/beto-sentiment-analysis](https://huggingface.co/finiteautomata/beto-sentiment-analysis)
+"""
+
+"""
 
 gr.Interface(
     predict_and_ctc_lm_decode,
@@ -35,7 +44,7 @@ gr.Interface(
     outputs=[gr.outputs.Textbox(label="Predicción")],
     examples=[["audio_test.wav"], ["sample_audio.wav"]],
     title="Sentiment Analysis of Spanish Transcribed Audio",
-    description="This is a Gradio demo for Sentiment Analysis of Transcribed Spanish Audio. First, we do Speech to Text, and then we perform sentiment analysis on the obtained transcription of the input audio.",
+    description=description,
     layout="horizontal",
     theme="huggingface",
 ).launch(enable_queue=True, cache_examples=True)