Update app.py

app.py

@@ -0,0 +1,31 @@
+from transformers import WhisperTokenizer
+
+tokenizer = WhisperTokenizer.from_pretrained("openai/whisper-small", language="marathi", task="transcribe")
+
+from transformers import pipeline
+import gradio as gr
+import torch 
+
+pipe = pipeline(model="thak123/whisper-small-gom", 
+                task="automatic-speech-recognition", tokenizer= tokenizer)  # change to "your-username/the-name-you-picked"
+
+pipe.model.config.forced_decoder_ids = (
+        pipe.tokenizer.get_decoder_prompt_ids(
+            language="marathi", task="transcribe"
+        )
+    )
+
+def transcribe(audio):
+    text = pipe(audio)["text"]
+    return text
+
+iface = gr.Interface(
+    fn=transcribe, 
+    inputs=gr.Audio(source="microphone", type="filepath"), 
+    outputs="text",
+    title="Whisper Small Konkani",
+    description="Realtime demo for Konkani speech recognition using a fine-tuned Whisper small model.",
+)
+
+
+iface.launch()