Automatic Speech Recognition
Transformers
PyTorch
wav2vec2
Generated from Trainer
Eval Results (legacy)
Instructions to use haseong8012/wav2vec2-large-xlsr-53_ko with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use haseong8012/wav2vec2-large-xlsr-53_ko with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="haseong8012/wav2vec2-large-xlsr-53_ko")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("haseong8012/wav2vec2-large-xlsr-53_ko") model = AutoModelForCTC.from_pretrained("haseong8012/wav2vec2-large-xlsr-53_ko", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6a9c06b60c3dddfefd445bed0bdfbe1628efa9f8a0efa2774fe8d5707fd63e8c
- Size of remote file:
- 1.27 GB
- SHA256:
- da8b7d81865ea8161cc3919bd41c35a26012f01531fb88c6aa3bbb66002b82ba
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