Automatic Speech Recognition
Transformers
PyTorch
speech-encoder-decoder
speech
xls_r
xls_r_translation
Instructions to use facebook/wav2vec2-xls-r-300m-21-to-en with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/wav2vec2-xls-r-300m-21-to-en with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="facebook/wav2vec2-xls-r-300m-21-to-en")# Load model directly from transformers import AutoTokenizer, AutoModelForSpeechSeq2Seq tokenizer = AutoTokenizer.from_pretrained("facebook/wav2vec2-xls-r-300m-21-to-en") model = AutoModelForSpeechSeq2Seq.from_pretrained("facebook/wav2vec2-xls-r-300m-21-to-en") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e2d0fbfadf1992a00045addd9225ca5d8e06d4843f6b83362b43fb813046346f
- Size of remote file:
- 3.17 GB
- SHA256:
- 02b827faddcf3cc3f0412f90423f5215e49f4dd42ef5765affd297e495334679
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