Automatic Speech Recognition
Transformers
PyTorch
Dutch
wav2vec2
hf-asr-leaderboard
model_for_talk
mozilla-foundation/common_voice_8_0
robust-speech-event
Eval Results (legacy)
Instructions to use Iskaj/xlsr_300m_CV_8.0_50_EP_new_params_nl with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Iskaj/xlsr_300m_CV_8.0_50_EP_new_params_nl with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Iskaj/xlsr_300m_CV_8.0_50_EP_new_params_nl")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("Iskaj/xlsr_300m_CV_8.0_50_EP_new_params_nl") model = AutoModelForCTC.from_pretrained("Iskaj/xlsr_300m_CV_8.0_50_EP_new_params_nl") - Notebooks
- Google Colab
- Kaggle
- Downloads last month
- 3
Evaluation results
- Test WER on Common Voice 8 NLself-reported35.440
- Test CER on Common Voice 8 NLself-reported19.570
- Test WER on Robust Speech Event - Dev Dataself-reported37.170
- Test WER on Robust Speech Event - Test Dataself-reported38.730