Update app.py

app.py

@@ -12,10 +12,10 @@ def load_and_fix_data(input_file, model_sampling_rate):
     return speech
 
 
-feature_extractor = AutoFeatureExtractor.from_pretrained("jonatasgrosman/wav2vec2-large-xlsr-53-spanish")
+feature_extractor = AutoFeatureExtractor.from_pretrained("jonatasgrosman/wav2vec2-xls-r-1b-spanish")
 sampling_rate = feature_extractor.sampling_rate
 
-asr = pipeline("automatic-speech-recognition", model="jonatasgrosman/wav2vec2-large-xlsr-53-spanish")
+asr = pipeline("automatic-speech-recognition", model="jonatasgrosman/wav2vec2-xls-r-1b-spanish")
 
 
 def predict_and_ctc_lm_decode(input_file):
@@ -26,6 +26,18 @@ def predict_and_ctc_lm_decode(input_file):
 
     return sexism_detection
 
+description = """    This is a Gradio demo for Spanish audio transcription-based Sexism detection. To use this, simply provide an audio input (audio recording or via microphone), which will subsequently be transcribed and classified as sexism/non-sexism pertaining to audio (transcription) with the help of pre-trained models.
+
+
+**NOTE: LABEL_0: "NON SEXISM" or LABEL_1: "SEXISM"**
+
+
+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 Sexism Detection : [hackathon-pln-es/twitter_sexismo-finetuned-robertuito-exist2021](https://huggingface.co/hackathon-pln-es/twitter_sexismo-finetuned-robertuito-exist2021)
+
+"""
+
 
 gr.Interface(
     predict_and_ctc_lm_decode,