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", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
transcribing chinese audio with the this model, the output text lacks punctuation
#103
by TaoGoblin - opened
When transcribing Chinese audio with the this model, the output text lacks punctuation. How can this be resolved?
Look at the post-processing with GPT-4 section.
But for this task, you can use any LLM. As for me, GPT-4 is not the best post-processor, I like Gemini, but you are not limited.
I also encountered the same problem and asked for a solution