Instructions to use esb/wav2vec2-aed-common_voice with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use esb/wav2vec2-aed-common_voice with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="esb/wav2vec2-aed-common_voice")# Load model directly from transformers import AutoTokenizer, AutoModelForSpeechSeq2Seq tokenizer = AutoTokenizer.from_pretrained("esb/wav2vec2-aed-common_voice") model = AutoModelForSpeechSeq2Seq.from_pretrained("esb/wav2vec2-aed-common_voice") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 67b3d27f7b42047a1a6595edfe17b68251546cf87db35e2fe702051d3f5d136d
- Size of remote file:
- 2.35 GB
- SHA256:
- 56b757915f96582822dd270ca71b4072ca18dd1d146515e733177fc7f1eb2ffb
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