Automatic Speech Recognition
Transformers
PyTorch
TensorFlow
JAX
Safetensors
English
whisper
audio
hf-asr-leaderboard
Eval Results (legacy)
Eval Results
Instructions to use openai/whisper-tiny.en with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use openai/whisper-tiny.en with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="openai/whisper-tiny.en")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("openai/whisper-tiny.en") model = AutoModelForSpeechSeq2Seq.from_pretrained("openai/whisper-tiny.en") - Notebooks
- Google Colab
- Kaggle
Commit History
Adding `safetensors` variant of this model (#21) 60c8e22
add timestamp tokens (#20) a652e21
add timestamp tokens (#19) 16436f6
Update generation config with word-level alignment heads (#16) b70535d
Update README.md 944489f
Update generation_config.json to suppress task tokens (#14) 329f3b1
Update config.json to suppress task tokens (#13) a63c560
Add Flax weights 1f7ce4a
sanchit-gandhi commited on