Automatic Speech Recognition
Transformers
PyTorch
wav2vec2
mozilla-foundation/common_voice_7_0
Generated from Trainer
Instructions to use jcmc/wav2vec2-large-xlsr-53-ir with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jcmc/wav2vec2-large-xlsr-53-ir with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="jcmc/wav2vec2-large-xlsr-53-ir")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("jcmc/wav2vec2-large-xlsr-53-ir") model = AutoModelForCTC.from_pretrained("jcmc/wav2vec2-large-xlsr-53-ir", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 24ec18066988db5749737e594e7373383c67bd216d7363b62878a8c23c6e703b
- Size of remote file:
- 2.99 kB
- SHA256:
- b1201627d2f6c171e3de950d42d9c110b925f203c1fa5b25c7cbb6313032710c
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