Automatic Speech Recognition
Transformers
PyTorch
JAX
Lithuanian
wav2vec2
audio
speech
xlsr-fine-tuning-week
Eval Results (legacy)
Instructions to use DeividasM/wav2vec2-large-xlsr-53-lithuanian with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DeividasM/wav2vec2-large-xlsr-53-lithuanian with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="DeividasM/wav2vec2-large-xlsr-53-lithuanian")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("DeividasM/wav2vec2-large-xlsr-53-lithuanian") model = AutoModelForCTC.from_pretrained("DeividasM/wav2vec2-large-xlsr-53-lithuanian") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4ca032e304d5249a4627a67f0d4e7c47a45216124a7677beda07da4adc2526b4
- Size of remote file:
- 1.26 GB
- SHA256:
- 1ca9162077d304fad237f6eed0e6b2f55f7d373120876552d8b1ca2c50991d2e
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