Create api.py

api.py

@@ -0,0 +1,17 @@
+from transformers import WhisperProcessor, WhisperForConditionalGeneration
+import torch
+import soundfile as sf
+
+class UrduWhisper:
+    def __init__(self):
+        print("Loading Urdu Whisper Tiny model...")
+        self.processor = WhisperProcessor.from_pretrained("kingabzpro/whisper-tiny-urdu")
+        self.model = WhisperForConditionalGeneration.from_pretrained("kingabzpro/whisper-tiny-urdu")
+        self.model.to("cpu")
+
+    def transcribe(self, audio_file):
+        audio, sr = sf.read(audio_file)
+        inputs = self.processor(audio, sampling_rate=sr, return_tensors="pt")
+        with torch.no_grad():
+            predicted_ids = self.model.generate(inputs["input_features"])
+        return self.processor.batch_decode(predicted_ids, skip_special_tokens=True)[0]