Automatic Speech Recognition
Transformers
PyTorch
Estonian
wav2vec2
audio
hf-asr-leaderboard
Eval Results (legacy)
Instructions to use TalTechNLP/xls-r-300m-et with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TalTechNLP/xls-r-300m-et with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="TalTechNLP/xls-r-300m-et")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("TalTechNLP/xls-r-300m-et") model = AutoModelForCTC.from_pretrained("TalTechNLP/xls-r-300m-et") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6ded658efb107393e7ac0661d5e22158a88373b55d23733fd7ced4a45299d575
- Size of remote file:
- 1.26 GB
- SHA256:
- 3ebb8bbc9f56a42858c9b69ed4b7a1b308ae623d7f8f1fc38788965dc638b106
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