Automatic Speech Recognition
Transformers
JAX
TensorBoard
ONNX
Safetensors
Transformers.js
English
whisper
audio
Eval Results
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", device_map="auto") - 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
- Xet hash:
- 4f088936c19a7f8594defa99cd1da8c60456f4b4f4b59effb2f8acbba9f7898c
- Size of remote file:
- 121 MB
- SHA256:
- ed5459e1147f9307de41adbc86bdfafe1672760b9c907cf9bc5c61398d9ba2a0
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