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
- Xet hash:
- 367f28e10ad49f67c9acac8f868066d97f1c9d58bba256c8f2b5eafdd0d7b766
- Size of remote file:
- 789 MB
- SHA256:
- 1ba7295420ad3e1ce2fe5f7e150b72f2adfd1f9f05925d806481a7391a8708ee
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