Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Russian
wav2vec2
audio
Generated from Trainer
hf-asr-leaderboard
mozilla-foundation/common_voice_8_0
robust-speech-event
speech
Eval Results (legacy)
Instructions to use RASMUS/wav2vec2-xlsr-1b-ru with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use RASMUS/wav2vec2-xlsr-1b-ru with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="RASMUS/wav2vec2-xlsr-1b-ru")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("RASMUS/wav2vec2-xlsr-1b-ru") model = AutoModelForCTC.from_pretrained("RASMUS/wav2vec2-xlsr-1b-ru", device_map="auto") - Notebooks
- Google Colab
- Kaggle
add eval ru without lm
Browse files- eval_ru_without_lm.sh +1 -0
eval_ru_without_lm.sh
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python eval.py --model_id RASMUS/wav2vec2-xlsr-1b-ru --dataset mozilla-foundation/common_voice_8_0 --config ru --split test --log_outputs
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