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
| {"unk_token": "[UNK]", "bos_token": "<s>", "eos_token": "</s>", "pad_token": "[PAD]", "do_lower_case": false, "word_delimiter_token": "|"} |