[docs] add quick usage snippet to Whisper. (#31289)

* [docs] add quick usage snippet to Whisper.

* Apply suggestions from review.

* 💉 Fix the device for pipeline.
This commit is contained in:
Vaibhav Srivastav
2024-08-27 14:11:52 +02:00
committed by GitHub
parent 892d51caee
commit 6f0ecf1049

View File

@@ -27,6 +27,27 @@ The abstract from the paper is the following:
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).
The original code can be found [here](https://github.com/openai/whisper).
## Quick usage
You can run Whisper in less than 4 lines of code and transcribe in less than a minute!
```python
# pip install transformers torch
import torch
from transformers import pipeline
whisper = pipeline("automatic-speech-recognition", "openai/whisper-large-v3", torch_dtype=torch.float16, device="cuda:0")
transcription = whisper("<audio_file.mp3>")
print(transcription["text"])
```
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.
Bonus: You can replace `"cuda"` with `"mps"` to make it seamlessly work on Macs.
## Usage tips
- The model usually performs well without requiring any finetuning.