Automatic Speech Recognition
Transformers
Safetensors
wav2vec2
Generated from Trainer
Eval Results (legacy)
Instructions to use dmusingu/XLS-R-SWAHILI-ASR-CV14 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dmusingu/XLS-R-SWAHILI-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-SWAHILI-ASR-CV14")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("dmusingu/XLS-R-SWAHILI-ASR-CV14") model = AutoModelForCTC.from_pretrained("dmusingu/XLS-R-SWAHILI-ASR-CV14", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 504dbfb29b84c303193fa7236703a1301a664f218bd71efb1e190d6e33fb56dc
- Size of remote file:
- 4.98 kB
- SHA256:
- 393c5687d56c9d1c6dfa561eb52a4104a15f389e1d479a35542dd692ed6c0e9d
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