Automatic Speech Recognition
Transformers
PyTorch
TensorFlow
JAX
Safetensors
whisper
audio
hf-asr-leaderboard
Eval Results (legacy)
Instructions to use openai/whisper-medium with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use openai/whisper-medium with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="openai/whisper-medium")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("openai/whisper-medium") model = AutoModelForSpeechSeq2Seq.from_pretrained("openai/whisper-medium", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Update the pad token (#12)
- Update the pad token (a1e2f26da25775b14466feec02888ab965f2f64d) Co-authored-by: Nicolas Patry <Narsil@users.noreply.huggingface.co>f1457a2
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Add Flax weights
sanchit-gandhi0d49445
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change hebrew code from iw (deprecated) to he (#8)
- change hebrew code from iw (deprecated) to he (106e8e1eaa5586609eeea0529217813730d8611c) Co-authored-by: Altryne <altryne@users.noreply.huggingface.co>8050949
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Upload config
eb2e18b