Update app.py

app.py

@@ -17,7 +17,7 @@ if os.path.exists(examples_dir):
             examples.append([os.path.join(examples_dir, filename)])
 
 # Load model and processor
-MODEL_PATH = "badrex/w2v-bert-2.0-kinyarwanda-asr"
+MODEL_PATH = "badrex/w2v-bert-2.0-amharic-asr"
 processor = AutoProcessor.from_pretrained(MODEL_PATH)
 model = AutoModelForCTC.from_pretrained(MODEL_PATH)
 
@@ -62,7 +62,7 @@ def process_audio(audio_path):
 
 # Define Gradio interface
 with gr.Blocks(title="ASRwanda") as demo:
-    gr.Markdown("# ASRwanda 🎙️ Speech Recognition for Kinyarwanda Language 🇷🇼")
+    gr.Markdown("# Amharic-ASR 🎙️ Speech Recognition for Amharic Language 🇪🇹")
     gr.Markdown("""
         <div class="centered-content">
             <div>
@@ -73,10 +73,7 @@ with gr.Blocks(title="ASRwanda") as demo:
                 <p style="font-size: 15px; line-height: 1.8;">
                  Muraho 👋🏼
                 <br><br>
-                 This is a demo for ASRwanda, a Transformer-based automatic speech recognition (ASR) system for Kinyarwanda language.
-                 The underlying ASR model was trained on 1000 hours of transcribed speech provided by 
-                 <a href="https://digitalumuganda.com/" style="color: #2563eb;">Digital Umuganda</a> as part of the Kinyarwanda
-                 <a href="https://www.kaggle.com/competitions/kinyarwanda-automatic-speech-recognition-track-b" style="color: #2563eb;"> ASR hackathon</a> on Kaggle.
+                 This is a demo for a Transformer-based automatic speech recognition (ASR) system for the Amharic language.
                 <br><br>                   
                 Simply <strong>upload an audio file</strong> 📤 or <strong>record yourself speaking</strong> 🎙️⏺️ to try out the model!
                 </p>