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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b0848a3f2c07cdfff53b00666528c95ea61784620c020f0a38c60922dfd0228f
- Size of remote file:
- 4.98 kB
- SHA256:
- a1a85cd9131a5a9bd9df1f041b762294cbf4467f73bb1f67622d0f158e7bcc95
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