Automatic Speech Recognition
Transformers
PyTorch
TensorFlow
JAX
Safetensors
English
whisper
audio
hf-asr-leaderboard
Eval Results (legacy)
Eval Results
Instructions to use openai/whisper-base.en with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use openai/whisper-base.en with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="openai/whisper-base.en")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("openai/whisper-base.en") model = AutoModelForSpeechSeq2Seq.from_pretrained("openai/whisper-base.en") - Notebooks
- Google Colab
- Kaggle
Commit History
add timestamp tokens (#15) 601d975
add timestamp tokens (#14) eb69268
Adding `safetensors` variant of this model (#13) 564c17e
Update generation config with word-level alignment heads (#12) efd3751
Update README.md 1773a19
Update generation_config.json to suppress task tokens (#8) 98672e2
Update config.json to suppress task tokens (#7) c1a81ce
Add Flax weights 2ae9a06
sanchit-gandhi commited on