Automatic Speech Recognition
Transformers
PyTorch
JAX
Lithuanian
wav2vec2
audio
speech
xlsr-fine-tuning-week
Eval Results (legacy)
Instructions to use m3hrdadfi/wav2vec2-large-xlsr-lithuanian with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use m3hrdadfi/wav2vec2-large-xlsr-lithuanian with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="m3hrdadfi/wav2vec2-large-xlsr-lithuanian")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("m3hrdadfi/wav2vec2-large-xlsr-lithuanian") model = AutoModelForCTC.from_pretrained("m3hrdadfi/wav2vec2-large-xlsr-lithuanian") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c1818a0dcbd227743347b92ac56d043776fc9ee9ee0f5a40abbdb37c3f671cb1
- Size of remote file:
- 2.42 kB
- SHA256:
- 52b6cdbecbe96c98fe75a15df0273a724242785d743da14d4ede050411b7f20a
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