Automatic Speech Recognition
Transformers
PyTorch
TensorFlow
JAX
Safetensors
English
whisper
audio
hf-asr-leaderboard
Eval Results (legacy)
Eval Results
Instructions to use openai/whisper-medium.en with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use openai/whisper-medium.en with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="openai/whisper-medium.en")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("openai/whisper-medium.en") model = AutoModelForSpeechSeq2Seq.from_pretrained("openai/whisper-medium.en") - Notebooks
- Google Colab
- Kaggle
Add Open ASR Leaderboard evaluation results
#19 opened about 2 months ago
by
SaylorTwift
Upload tokenizer.json
#18 opened 9 months ago
by
jakmro
Can I use flash attention 2 with this model?
1
#15 opened over 2 years ago
by
anuragrawal
Correct added token ids
#14 opened over 2 years ago
by
sanchit-gandhi
WhisperTimeStampLogitsProcessor error while using Whisper pipelines happens with this model
#9 opened about 3 years ago
by
icorbett