Automatic Speech Recognition
Transformers
PyTorch
wav2vec2
mozilla-foundation/common_voice_7_0
Generated from Trainer
Instructions to use jcmc/wav2vec2-xls-r-1b-ir with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jcmc/wav2vec2-xls-r-1b-ir with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="jcmc/wav2vec2-xls-r-1b-ir")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("jcmc/wav2vec2-xls-r-1b-ir") model = AutoModelForCTC.from_pretrained("jcmc/wav2vec2-xls-r-1b-ir", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7657f24763e1a4c4902a257f5ed918ee345a5dc9a6cad267153e6880bad1bce6
- Size of remote file:
- 3.85 GB
- SHA256:
- c3f95ed8ef93813000919e4761a0f98ff8bf469c62dafa28feca9ae8d4491bcc
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