Automatic Speech Recognition
Transformers
PyTorch
JAX
TensorBoard
ONNX
Safetensors
Transformers.js
English
whisper
audio
Eval Results
Instructions to use distil-whisper/distil-medium.en with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use distil-whisper/distil-medium.en with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="distil-whisper/distil-medium.en")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("distil-whisper/distil-medium.en") model = AutoModelForSpeechSeq2Seq.from_pretrained("distil-whisper/distil-medium.en") - Transformers.js
How to use distil-whisper/distil-medium.en with Transformers.js:
// npm i @huggingface/transformers import { pipeline } from '@huggingface/transformers'; // Allocate pipeline const pipe = await pipeline('automatic-speech-recognition', 'distil-whisper/distil-medium.en'); - Notebooks
- Google Colab
- Kaggle
small, tiny, base models
#7
by eschmidbauer - opened
Thank you for sharing this code!
Any plans to release small, tiny or base models?
I'm testing medium in-browser using onnx + transformers.js and it's still too slow.
Wondering if any of the smaller models will be available for further testing of in-browser inference.
I found Whisper CPP to be very performant: https://huggingface.co/distil-whisper/distil-medium.en#whispercpp
Not sure if you can run this in-browser, but the CPU-only performance is great.
Training 2 decoder layer versions of small.en now!
thanks!
eschmidbauer changed discussion status to closed