Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Yakut
wav2vec2
Generated from Trainer
robust-speech-event
hf-asr-leaderboard
Eval Results (legacy)
Instructions to use emre/wav2vec2-xls-r-300m-W2V2-XLSR-300M-YAKUT-SMALL with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use emre/wav2vec2-xls-r-300m-W2V2-XLSR-300M-YAKUT-SMALL with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="emre/wav2vec2-xls-r-300m-W2V2-XLSR-300M-YAKUT-SMALL")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("emre/wav2vec2-xls-r-300m-W2V2-XLSR-300M-YAKUT-SMALL") model = AutoModelForCTC.from_pretrained("emre/wav2vec2-xls-r-300m-W2V2-XLSR-300M-YAKUT-SMALL", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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