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")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("openai/whisper-medium") model = AutoModelForSpeechSeq2Seq.from_pretrained("openai/whisper-medium") - Notebooks
- Google Colab
- Kaggle
Commit ·
ef26027
1
Parent(s): 3aafc0f
Add TF weights (#1)
Browse files- Add TF weights (83301bbc16683580195c364b3c64c573ab6c9125)
- tf_model.h5 +3 -0
tf_model.h5
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oid sha256:a0719162ff90716276ee4cceb13b8bb6fc87601bb71a6b0bfdde08708c9fe550
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