Instructions to use HuyenNguyen/Wav2vec with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HuyenNguyen/Wav2vec with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="HuyenNguyen/Wav2vec")# Load model directly from transformers import AutoTokenizer, AutoModelForSpeechSeq2Seq tokenizer = AutoTokenizer.from_pretrained("HuyenNguyen/Wav2vec") model = AutoModelForSpeechSeq2Seq.from_pretrained("HuyenNguyen/Wav2vec") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 49eaa3198759347e334ad7f0c9951cb603e6c65164bf458743353ed11d5fe458
- Size of remote file:
- 135 Bytes
- SHA256:
- 27dc020061122a4c4d162f08ca41ba37d62525b82b4ab5309898c9a268f63f61
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.