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:
- a40c5bbb74b6ee48b71e6065b54455ee2e739f18bffc141e649d324b0f0321be
- Size of remote file:
- 3.12 kB
- SHA256:
- 33d410e2e8f54573045bed2df4cfad2a10091c914e24b2b2aa846ae8cce08cbe
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