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
Add Open ASR Leaderboard evaluation results
#18 opened about 1 month ago
by
SaylorTwift
Correct added token ids
#16 opened over 2 years ago
by
sanchit-gandhi
Missing log files after training finished
2
#11 opened almost 3 years ago
by
fkov
Update README.md
#10 opened almost 3 years ago
by
Jesuscarr
Noise Level
1
#9 opened about 3 years ago
by
MemberDS