Update app.py

app.py

@@ -1,18 +1,3 @@
 import gradio as gr
-from transformers import WhisperProcessor, WhisperForConditionalGeneration
-import torchaudio
 
-# Load model and processor
-model_id = "heisenberg3376/whisper-small-finetuned-telugu"
-processor = WhisperProcessor.from_pretrained(model_id)
-model = WhisperForConditionalGeneration.from_pretrained(model_id)
-
-def transcribe(audio_path):
-    waveform, sr = torchaudio.load(audio_path)
-    if sr != 16000:
-        waveform = torchaudio.transforms.Resample(sr, 16000)(waveform)
-    input_feats = processor(waveform.squeeze(), sampling_rate=16000, return_tensors="pt").input_features
-    pred_ids = model.generate(input_feats)
-    return str(processor.decode(pred_ids[0], skip_special_tokens=True))
-
-gr.Interface(fn=transcribe, inputs=gr.Audio(type="filepath"), outputs="text", title="Telugu ASR").launch()
+gr.load("heisenberg3376/whisper-small-finetuned-telugu").launch()