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, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("openai/whisper-small.en") model = AutoModelForSpeechSeq2Seq.from_pretrained("openai/whisper-small.en") - Notebooks
- Google Colab
- Kaggle
File size: 134 Bytes
287fee8 | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:f1c8d569697781d484a4516315806f6f97d4fe5ff2d62789dc351909f16ebd92
size 966953755
|