Instructions to use pirxus/wav2vec2_s2t_encoder_base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pirxus/wav2vec2_s2t_encoder_base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="pirxus/wav2vec2_s2t_encoder_base")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("pirxus/wav2vec2_s2t_encoder_base") model = AutoModelForCTC.from_pretrained("pirxus/wav2vec2_s2t_encoder_base") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0071cf94f65ecb84c3f6f6f9ed8c2e31787fb58463370c23aec57b6b555287db
- Size of remote file:
- 82.7 MB
- SHA256:
- 9080c19456cca99c92244baee0d811e4ebbd841e0cc70eccde7febe32fc693fb
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