Instructions to use distil-whisper/distil-large-v3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use distil-whisper/distil-large-v3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="distil-whisper/distil-large-v3")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("distil-whisper/distil-large-v3") model = AutoModelForSpeechSeq2Seq.from_pretrained("distil-whisper/distil-large-v3") - Transformers.js
How to use distil-whisper/distil-large-v3 with Transformers.js:
// npm i @huggingface/transformers import { pipeline } from '@huggingface/transformers'; // Allocate pipeline const pipe = await pipeline('automatic-speech-recognition', 'distil-whisper/distil-large-v3'); - Notebooks
- Google Colab
- Kaggle
about multiple languages?
Someone has already asked this, but I still want to ask: is it possible to support multiple languages output simultaneously, like mixing several languages in speech?
Thanks a lot
The checkpoints on the distil-whisper organisation on the Hub currently only support English. However, it's possible to distil Whisper models in languages of your choice. See the provided training code and this checkpoint as examples. You can quite easily extend this code to train the model on multiple languages to do language switching within an utterance.
the behavior for non-English language is comfusing, if i use the model to transcribe a japanese audio without setting language paramenter, it can do it but always translate result to english