Automatic Speech Recognition
Transformers
PyTorch
JAX
Kyrgyz
wav2vec2
audio
speech
xlsr-fine-tuning-week
Eval Results (legacy)
Instructions to use kyrgyz-ai/Wav2vec-Kyrgyz with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kyrgyz-ai/Wav2vec-Kyrgyz with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="kyrgyz-ai/Wav2vec-Kyrgyz")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("kyrgyz-ai/Wav2vec-Kyrgyz") model = AutoModelForCTC.from_pretrained("kyrgyz-ai/Wav2vec-Kyrgyz") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2300158ebfb2d7de9b6d67ae612abbdce987a1e80d09fec36781407b483de5c6
- Size of remote file:
- 1.26 GB
- SHA256:
- 46e70a0b38ee06dd3938318bbccf2ced497e11cae6810ce5a5aa85a33e232f36
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