Instructions to use openai/whisper-large-v3-turbo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use openai/whisper-large-v3-turbo with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="openai/whisper-large-v3-turbo")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("openai/whisper-large-v3-turbo") model = AutoModelForSpeechSeq2Seq.from_pretrained("openai/whisper-large-v3-turbo") - Inference
- Notebooks
- Google Colab
- Kaggle
Benchmarks against distil-whisper/distil-large-v3?
#40
by datasaurus - opened
Does anyone have any latency metrics comparing v3-turbo against distil-whisper/distil-large-v3?
Not an exhaustive test, but on an RTX 3090 with flash attention 2, 100 minutes of audio:
distil-whisper/distil-large-v3 = 2 m 17s
openai/whisper-large-v3-turbo = 2m 59s