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")# pip install -U transformers accelerate # 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", device_map="auto") - 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
Download original-model.bin from distil-whisper/distil-medium.en: direct link, hf CLI and curl.
- Browser
- Download file 789 MB
-
https://huggingface.co/distil-whisper/distil-medium.en/resolve/main/original-model.bin
- Command line
-
hf download hf://distil-whisper/distil-medium.en/original-model.bin
-
curl -L -o original-model.bin https://huggingface.co/distil-whisper/distil-medium.en/resolve/main/original-model.bin
789 MB
- Xet hash:
- b496f45411e29578fca483429c96c4cf8ae71380aed061e0c6537a0c15c54c8e
- Size of remote file:
- 789 MB
- SHA256:
- 01e13e93f66fb9f17e8cd766743fa1dc13f3edd3f81eba351dbb07829619fc94
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