[docs] add quick usage snippet to Whisper. (#31289)
* [docs] add quick usage snippet to Whisper.
* Apply suggestions from review.
* 💉 Fix the device for pipeline.
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@@ -27,6 +27,27 @@ The abstract from the paper is the following:
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This model was contributed by [Arthur Zucker](https://huggingface.co/ArthurZ). The Tensorflow version of this model was contributed by [amyeroberts](https://huggingface.co/amyeroberts).
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The original code can be found [here](https://github.com/openai/whisper).
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## Quick usage
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You can run Whisper in less than 4 lines of code and transcribe in less than a minute!
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```python
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# pip install transformers torch
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import torch
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from transformers import pipeline
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whisper = pipeline("automatic-speech-recognition", "openai/whisper-large-v3", torch_dtype=torch.float16, device="cuda:0")
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transcription = whisper("<audio_file.mp3>")
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print(transcription["text"])
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```
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Voila! You can swap the model with any [Whisper checkpoints](https://huggingface.co/models?other=whisper&sort=downloads) on the Hugging Face Hub with the same pipeline based on your needs.
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Bonus: You can replace `"cuda"` with `"mps"` to make it seamlessly work on Macs.
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## Usage tips
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- The model usually performs well without requiring any finetuning.
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