[docs] Updates trace whisper model document (#3426)

examples/docs/whisper_speech_text.md

@@ -25,7 +25,8 @@ Output:
 
 ## Trace the model
 
-You can use the following script to get the traced model and also vocabulary files:
+You can use the following script to get the traced model and also vocabulary files, this script works
+with `transformers==4.38.0`
 
 ```python
 from transformers import WhisperProcessor, WhisperForConditionalGeneration
@@ -35,7 +36,11 @@ import numpy as np
 
 processor = WhisperProcessor.from_pretrained("openai/whisper-base")
 processor.tokenizer.save_pretrained("whisper-tokenizer")
-model = WhisperForConditionalGeneration.from_pretrained("openai/whisper-base", return_dict=False)
+model = WhisperForConditionalGeneration.from_pretrained("openai/whisper-base", torchscript=True, attn_implementation="eager")
+model.generation_config.language = "en"
+model.generation_config.task = "transcribe"
+model.generation_config.forced_decoder_ids = None
+
 ds = load_dataset("hf-internal-testing/librispeech_asr_dummy", "clean", split="validation")
 
 test = []
@@ -45,13 +50,13 @@ for ele in ds:
 input_features = processor(np.concatenate(test), return_tensors="pt").input_features
 generated_ids = model.generate(inputs=input_features)
 transcription = processor.batch_decode(generated_ids, skip_special_tokens=True)[0]
-print("Original: " + transcription)
+print(f"Original: {transcription}")
 
 # Start tracing
 traced_model = torch.jit.trace_module(model, {"generate": [input_features]})
 generated_ids = traced_model.generate(input_features)
 transcription = processor.batch_decode(generated_ids, skip_special_tokens=True)[0]
-print("Traced: " + transcription)
+print(f"Traced: {transcription}")
 
 torch.jit.save(traced_model, "whisper_en.pt")
 ```