Automatic Speech Recognition
Transformers
PyTorch
TensorFlow
JAX
Safetensors
whisper
audio
hf-asr-leaderboard
Eval Results (legacy)
Eval Results
Instructions to use openai/whisper-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use openai/whisper-large with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="openai/whisper-large")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("openai/whisper-large") model = AutoModelForSpeechSeq2Seq.from_pretrained("openai/whisper-large") - Notebooks
- Google Colab
- Kaggle
Audio file is not transcribed after 30 second mark.
#16
by kirankumaram - opened
Audio is transcribed or translated only till the 30 second mark for a 3-minute input file. Followed the same procedure as mentioned in the model card. Kindly help
Issue is solved if we use pipeline mentioned in https://huggingface.co/openai/whisper-large-v2/discussions/7#6398809b11095028d87b16a2.
But if we use the pipeline mentioned in model-card, transcription is not taking place after 30 second mark