Automatic Speech Recognition
Transformers
PyTorch
JAX
Safetensors
whisper
audio
hf-asr-leaderboard
Eval Results
Instructions to use openai/whisper-large-v3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use openai/whisper-large-v3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="openai/whisper-large-v3")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("openai/whisper-large-v3") model = AutoModelForSpeechSeq2Seq.from_pretrained("openai/whisper-large-v3") - Inference
- Notebooks
- Google Colab
- Kaggle
Code Switching using Whisper-large-v3
#207
by indrasn0wal - opened
Is it possible to do code switching using Whisper? I saw few blogs, where it was mentioned not possible. So I tried on hinglish data, and it is giving good results. Although not fully accurate but it is giving good results. So, I think naturally it can perform code switching, only for low resource languages, it will require fine-tuning.
Colab Notebook: https://colab.research.google.com/drive/1m2CnUTYlEroYoTPoZx37BRpUwSSAa215?usp=sharing