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") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0e99e01c7281aa0486830c9c5fc81033736a927bfb3cec8d88b386365f6f02f3
- Size of remote file:
- 1.26 GB
- SHA256:
- 63bcba61f33eca8105f4d85d373479b57b095711041e517b6532ad338a0617b9
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