Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Estonian
wav2vec2
Generated from Trainer
mozilla-foundation/common_voice_8_0
audio
speech
robust-speech-event
hf-asr-leaderboard
Eval Results (legacy)
Instructions to use RASMUS/wav2vec2-xlsr-1b-et with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use RASMUS/wav2vec2-xlsr-1b-et with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="RASMUS/wav2vec2-xlsr-1b-et", device_map="auto")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("RASMUS/wav2vec2-xlsr-1b-et") model = AutoModelForCTC.from_pretrained("RASMUS/wav2vec2-xlsr-1b-et", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Welcome to the community
The community tab is the place to discuss and collaborate with the HF community!