Automatic Speech Recognition
Transformers
PyTorch
TensorFlow
JAX
Safetensors
whisper
audio
hf-asr-leaderboard
Eval Results (legacy)
Instructions to use openai/whisper-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use openai/whisper-small with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="openai/whisper-small", device_map="auto")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("openai/whisper-small") model = AutoModelForSpeechSeq2Seq.from_pretrained("openai/whisper-small", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit ·
e34e8ae
1
Parent(s): b93f5c7
add special tokens for fast (#33)
Browse files- add special tokens for fast (59deef86e24136770a848f1c22f4bd17af422e39)
- tokenizer.json +0 -0
- vocab.json +0 -0
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vocab.json
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