Automatic Speech Recognition
Transformers
PyTorch
JAX
Yue Chinese
wav2vec2
audio
speech
xlsr-fine-tuning-week
Eval Results (legacy)
Instructions to use ctl/wav2vec2-large-xlsr-cantonese with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ctl/wav2vec2-large-xlsr-cantonese with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="ctl/wav2vec2-large-xlsr-cantonese")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("ctl/wav2vec2-large-xlsr-cantonese") model = AutoModelForCTC.from_pretrained("ctl/wav2vec2-large-xlsr-cantonese") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 61548455863f5d2b4b9a9847978f5f5cc84aa44bbbca634faaf419583d9d2beb
- Size of remote file:
- 1.28 GB
- SHA256:
- be24b09e034b87ca13dbe80e6ed94a927a4e964a3b5e0909c88e0553a2f71636
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