| 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] |