whisper identified the wrong language
### Feature request

When I follow the example of long-form transcription for whisper-large with Korean, the result is English. But after finetuning the whisper-large model with some Korean data, the checkpoint can output Korean. I also test other model size, but all the models output English. 
I was confused about it. How should I do to output Korean with the original model? 
Thank you!

### Motivation

Test whisper in Korean.

### Your contribution

Test whisper in Korean.
Hi there. Questions like this are better suited on the [forums](https://discuss.huggingface.co/) or a discussion on the model page as we keep issues for bugs and feature requests only.<|||||>If you use pipeline, you should add option like 
generate_kwargs = {"task":"transcribe", "language":"<|fr|>"}


ref1: https://colab.research.google.com/drive/1rS1L4YSJqKUH_3YxIQHBI982zso23wor#scrollTo=dPD20IkEDsbG
ref2: https://github.com/huggingface/transformers/issues/22331

however, I think default task should be "transcribe" not "translate". I insist It's an error.<|||||>I have solved the problem.
Step 1: Upgrade transformers, unfixed.
Step 2: Add option like "generate_kwargs = {"task":"transcribe", "language":"<|fr|>"}", unfixed.
Step 3: Add a line like "pipe.model.config.forced_decoder_ids = pipe.tokenizer.get_decoder_prompt_ids(language="ko", task="transcribe")", fixed.

However, I still don't understand why the original model output is English but the fine-tuned model output is in Korean.<|||||>maybe you can checked your fine-tuned model's config.json  or generation_config.json, double check the default task type, I think it's null or "transcribe"<|||||>This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.

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