Instructions to use facebook/wav2vec2-base-lv-voxpopuli-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/wav2vec2-base-lv-voxpopuli-v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="facebook/wav2vec2-base-lv-voxpopuli-v2")# Load model directly from transformers import AutoProcessor, AutoModelForPreTraining processor = AutoProcessor.from_pretrained("facebook/wav2vec2-base-lv-voxpopuli-v2") model = AutoModelForPreTraining.from_pretrained("facebook/wav2vec2-base-lv-voxpopuli-v2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c010fe4eae581c5a27c9ad8e5b97e990f18024010e124869ce803104936a947b
- Size of remote file:
- 380 MB
- SHA256:
- 006a1edd2e9fc6a75722c2cd75015d04e4219bacf64756811e4469f0bc8665e1
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