Automatic Speech Recognition
Transformers
PyTorch
JAX
TensorBoard
ONNX
Safetensors
Transformers.js
English
whisper
audio
Eval Results
Instructions to use distil-whisper/distil-large-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use distil-whisper/distil-large-v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="distil-whisper/distil-large-v2")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("distil-whisper/distil-large-v2") model = AutoModelForSpeechSeq2Seq.from_pretrained("distil-whisper/distil-large-v2", device_map="auto") - Transformers.js
How to use distil-whisper/distil-large-v2 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-v2'); - Notebooks
- Google Colab
- Kaggle
Wisper cpp
#8
by faria - opened
I found out a model using cpp maybe can help on development
https://github.com/ggerganov/whisper.cpp
and a python wrapper
https://git.ecker.tech/lightmare/whispercpp.py
Added some instructions for running in Whisper CPP: https://huggingface.co/distil-whisper/distil-large-v2#whispercpp
Let me know if that helps!