Create app.py

app.py

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+from transformers import WhisperProcessor, WhisperForConditionalGeneration
+import librosa
+
+# Load model and processor
+device = "cuda"
+processor = WhisperProcessor.from_pretrained("jiviai/audioX-south-v1")
+model = WhisperForConditionalGeneration.from_pretrained("jiviai/audioX-south-v1").to(device)
+model.config.forced_decoder_ids = None
+
+# Load and preprocess audio
+audio_path = "sample.wav"
+audio_np, sr = librosa.load(audio_path, sr=None)
+if sr != 16000:
+    audio_np = librosa.resample(audio_np, orig_sr=sr, target_sr=16000)
+
+input_features = processor(audio_np, sampling_rate=16000, return_tensors="pt").to(device).input_features
+
+# Generate predictions
+# Use ISO 639-1 language codes: "hi", "mr", "gu" for North; "ta", "te", "kn", "ml" for South
+# Or omit the language argument for automatic language detection
+predicted_ids = model.generate(input_features, task="transcribe", language="ta")
+
+# Decode predictions
+transcription = processor.batch_decode(predicted_ids, skip_special_tokens=True)[0]
+print(transcription)