Automatic Speech Recognition
Transformers
PyTorch
wav2vec2
Generated from Trainer
Eval Results (legacy)
Instructions to use jcrkn/wav2vec2-large-xls-r-300m-bretonwelsh-colab with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jcrkn/wav2vec2-large-xls-r-300m-bretonwelsh-colab with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="jcrkn/wav2vec2-large-xls-r-300m-bretonwelsh-colab")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("jcrkn/wav2vec2-large-xls-r-300m-bretonwelsh-colab") model = AutoModelForCTC.from_pretrained("jcrkn/wav2vec2-large-xls-r-300m-bretonwelsh-colab", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 43b887e265f2ca131485ad4ae6870dec2e1d26070bef55006d0ae7c98db04e1d
- Size of remote file:
- 1.26 GB
- SHA256:
- bf7a68ebf4a94a663b9f23c54d63ad9fee40f04cfeac6438527221d343e483f5
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