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
Commit ·
b22d3c1
1
Parent(s): f364131
Upload tokenizer.json
Browse filesGenerated with:
```python
from transformers import AutoTokenizer
tokenizer = AutoTokenizer.from_pretrained("openai/whisper-large-v3")
assert tokenizer.is_fast
tokenizer.save_pretrained("...")
```
- tokenizer.json +0 -0
tokenizer.json
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