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facebook
/
wav2vec2-large-960h

Automatic Speech Recognition
Transformers
PyTorch
English
wav2vec2
speech
Eval Results
Model card Files Files and versions
xet
Community
7

Instructions to use facebook/wav2vec2-large-960h with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use facebook/wav2vec2-large-960h with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("automatic-speech-recognition", model="facebook/wav2vec2-large-960h")
    # Load model directly
    from transformers import AutoProcessor, AutoModelForCTC
    
    processor = AutoProcessor.from_pretrained("facebook/wav2vec2-large-960h")
    model = AutoModelForCTC.from_pretrained("facebook/wav2vec2-large-960h")
  • Notebooks
  • Google Colab
  • Kaggle
New discussion
Resources
  • PR & discussions documentation
  • Code of Conduct
  • Hub documentation

Add Open ASR Leaderboard evaluation results

#7 opened about 1 month ago by
SaylorTwift

Adding `safetensors` variant of this model

#6 opened 8 months ago by
SFconvertbot

how to fine-tune to the ultimate performance? I only got 2.9% on test-clean

😔 1
#5 opened 10 months ago by
wesfggfd

Update README.md

#4 opened over 2 years ago by
sanchit-gandhi

Adding `safetensors` variant of this model

#3 opened about 3 years ago by
SFconvertbot

Example code fixed

#2 opened over 3 years ago by
samyxdev

Wav2vec2 finetuning - Evaluation WER does not change

1
#1 opened almost 4 years ago by
thardindubph200
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