Update README.md

README.md

@@ -104,13 +104,13 @@ arr, sampling_rate = librosa.load(file, sr=16000)
 
 # Load whisper model and processor
 processor = WhisperProcessor.from_pretrained("openai/whisper-small")
-model = WhisperForConditionalGeneration.from_pretrained("vimey/whispered_TIA_small_ad_tokenization_encoder_freezing_normal")
+model = WhisperForConditionalGeneration.from_pretrained("masters-thesis-vm/whispered_TIA_small_ad_tokenization_encoder_freezing_normal")
 
 # Preprocessing
 input_features = processor(arr, return_tensors="pt", sampling_rate=sampling_rate).input_features 
 
 # Prediction
-forced_decoder_ids = processor.get_decoder_prompt_ids(language="ko", task="transcribe")
+forced_decoder_ids = processor.get_decoder_prompt_ids(language="en", task="transcribe")
 predicted_ids = model.generate(input_features, forced_decoder_ids=forced_decoder_ids)
 transcription = processor.batch_decode(predicted_ids, skip_special_tokens=True)