Automatic Speech Recognition
Transformers
PyTorch
TensorFlow
JAX
Safetensors
whisper
audio
hf-asr-leaderboard
Eval Results
Instructions to use openai/whisper-large-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use openai/whisper-large-v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="openai/whisper-large-v2")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("openai/whisper-large-v2") model = AutoModelForSpeechSeq2Seq.from_pretrained("openai/whisper-large-v2") - Notebooks
- Google Colab
- Kaggle
About length of audio input to the model
#73
by sanjitaa - opened
I am using inference API of this largev2 model but the problem is it only transcribes audio of 3o sec. I want to transcribe the audio more than 30 sec through inference API of this model . How to solve this ?
Please help me out with it..
I don't think it's possible with the current inference API: https://huggingface.co/docs/api-inference/detailed_parameters#automatic-speech-recognition-task
Maybe @reach-vb can advise on how to bypass this?