Update app.py

app.py

@@ -1,45 +1,23 @@
-# from transformers import pipeline
-# import gradio as gr
+from transformers import pipeline
 
+model_id = "tarteel-ai/whisper-base-ar-quran"  
+pipe = pipeline("automatic-speech-recognition", model=model_id)
 
-# # Load the pipeline with the cache_dir parameter
-# pipe = pipeline(model="tarteel-ai/whisper-base-ar-quran")
+def transcribe(filepath):
+    output = pipe(
+        filepath,
+        max_new_tokens=10000,
+        chunk_length_s=30,
+        batch_size=8,
+    )
+    return output["text"]
 
-# def transcribe(audio):
-#     text = pipe(audio)["text"]
-#     return text
-
-# iface = gr.Interface(
-#     fn=transcribe,
-#     inputs=gr.Audio(source="upload", type="filepath"),
-#     outputs="text",
-# )
-
-# iface.launch()
-
-
-
-# from transformers import pipeline
-
-# model_id = "tarteel-ai/whisper-base-ar-quran"  # update with your model id
-# pipe = pipeline("automatic-speech-recognition", model=model_id)
-
-# def transcribe(filepath):
-#     output = pipe(
-#         filepath,
-#         max_new_tokens=10000,
-#     )
-#     return output["text"]
-
-# import gradio as gr
-
-# iface = gr.Interface(
-#     fn=transcribe,
-#     inputs=gr.Audio(source="upload", type="filepath"),
-#     outputs="text",
-# )
-
-# iface.launch()
 import gradio as gr
 
-gr.Interface.load("models/tarteel-ai/whisper-base-ar-quran").launch()
+iface = gr.Interface(
+    fn=transcribe,
+    inputs=gr.Audio(source="upload", type="filepath"),
+    outputs="text",
+)
+
+iface.launch()