Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Safetensors
Uyghur
wav2vec2
Generated from Trainer
hf-asr-leaderboard
mozilla-foundation/common_voice_8_0
robust-speech-event
Eval Results (legacy)
Instructions to use lucio/xls-r-uyghur-cv8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lucio/xls-r-uyghur-cv8 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="lucio/xls-r-uyghur-cv8")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("lucio/xls-r-uyghur-cv8") model = AutoModelForCTC.from_pretrained("lucio/xls-r-uyghur-cv8") - Notebooks
- Google Colab
- Kaggle
| { | |
| "epoch": 99.99, | |
| "eval_loss": 0.20258904993534088, | |
| "eval_runtime": 135.1965, | |
| "eval_samples": 2744, | |
| "eval_samples_per_second": 20.296, | |
| "eval_steps_per_second": 2.537, | |
| "eval_wer": 0.3247906274312388 | |
| } |