Instructions to use Yilin0601/wav2vec2-fluency-checkpoints with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Yilin0601/wav2vec2-fluency-checkpoints with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="Yilin0601/wav2vec2-fluency-checkpoints")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("Yilin0601/wav2vec2-fluency-checkpoints") model = AutoModelForAudioClassification.from_pretrained("Yilin0601/wav2vec2-fluency-checkpoints") - Notebooks
- Google Colab
- Kaggle
- Size of remote file:
- 5.3 kB
- SHA256:
- 8f8869bbdbdf813602aa221fe8cd0a4e75205c690343d49a2dccb38ac4dfafcc
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