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
xls-r-uyghur-cv8 / runs /Feb03_08-05-51_job-699ba53c-fea9-4eb2-81af-a97f440eaa45 /events.out.tfevents.1643875596.job-699ba53c-fea9-4eb2-81af-a97f440eaa45.626095.0
- Xet hash:
- e0b038bd1b6baacbe88fa089737b493f236b874ab12895bb6c5bea8fa41fc56c
- Size of remote file:
- 27.6 kB
- SHA256:
- 382118c1508603f2b5c052f0bbf5e016ea65eba25e2b3a2f2001f7d2b98e85ee
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