Automatic Speech Recognition
Transformers
PyTorch
TensorFlow
JAX
English
wav2vec2
speech
audio
hf-asr-leaderboard
Eval Results (legacy)
Eval Results
Instructions to use facebook/wav2vec2-large-960h-lv60-self with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/wav2vec2-large-960h-lv60-self with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="facebook/wav2vec2-large-960h-lv60-self")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("facebook/wav2vec2-large-960h-lv60-self") model = AutoModelForCTC.from_pretrained("facebook/wav2vec2-large-960h-lv60-self") - Notebooks
- Google Colab
- Kaggle
Ctrl+K