Automatic Speech Recognition
Transformers
PyTorch
TensorFlow
Safetensors
English
wav2vec2
audio
hf-asr-leaderboard
Eval Results (legacy)
Eval Results
Instructions to use facebook/wav2vec2-base-960h with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/wav2vec2-base-960h with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="facebook/wav2vec2-base-960h")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("facebook/wav2vec2-base-960h") model = AutoModelForCTC.from_pretrained("facebook/wav2vec2-base-960h") - Notebooks
- Google Colab
- Kaggle
Commit History
Remove `soundfile` import (#2) 7061117
Update README.md 55bb623
Update README.md 7ee7fd3
Update README.md c0b7a4a
Update README.md 5962bda
Update README.md 8833830
Update README.md 5e3d456
Upload README.md 7717449
Update README.md 6b154c5
Update README.md f1f1647
allow flax 67fb590
Patrick von Platen commited on