Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Georgian
wav2vec2
mozilla-foundation/common_voice_8_0
Generated from Trainer
robust-speech-event
hf-asr-leaderboard
Eval Results (legacy)
Instructions to use arampacha/wav2vec2-xls-r-1b-ka with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use arampacha/wav2vec2-xls-r-1b-ka with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="arampacha/wav2vec2-xls-r-1b-ka")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("arampacha/wav2vec2-xls-r-1b-ka") model = AutoModelForCTC.from_pretrained("arampacha/wav2vec2-xls-r-1b-ka") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4da8b6582d0154ca8129057cee54c02ad321d91308972ca3df8310502ef1db4e
- Size of remote file:
- 3.85 GB
- SHA256:
- 212f57547af3137f2f8ebac216bdca410c0a8c54c3af522454fe65cb767037da
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