Automatic Speech Recognition
Transformers
PyTorch
TensorFlow
JAX
Safetensors
English
whisper
audio
hf-asr-leaderboard
Eval Results (legacy)
Eval Results
Instructions to use openai/whisper-small.en with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use openai/whisper-small.en with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="openai/whisper-small.en")# Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("openai/whisper-small.en") model = AutoModelForMultimodalLM.from_pretrained("openai/whisper-small.en") - Notebooks
- Google Colab
- Kaggle
Commit ·
8cf2071
1
Parent(s): f402f31
add timestamp tokens (#14)
Browse files- add timestamp tokens (48734f0406997241e49691a11f33557e1ced374c)
- tokenizer.json +0 -0
- vocab.json +0 -0
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vocab.json
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