Automatic Speech Recognition
Transformers
Safetensors
wav2vec2
Generated from Trainer
Eval Results (legacy)
Instructions to use dmusingu/XLS-R-LUGANDA-ASR-CV14 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dmusingu/XLS-R-LUGANDA-ASR-CV14 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="dmusingu/XLS-R-LUGANDA-ASR-CV14")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("dmusingu/XLS-R-LUGANDA-ASR-CV14") model = AutoModelForCTC.from_pretrained("dmusingu/XLS-R-LUGANDA-ASR-CV14") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4dcfa72ce104f5c8426fbba1ddabc93711e83d95c8610fb2edcc237a319dc281
- Size of remote file:
- 3.85 GB
- SHA256:
- 8afe5c94fa8406c833091a3faeece52b8718861c35cd993d337d2ca0155229e5
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