Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Kinyarwanda
whisper
whisper-event
Generated from Trainer
Eval Results (legacy)
Instructions to use Kleber/output_dir with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Kleber/output_dir with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Kleber/output_dir")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Kleber/output_dir") model = AutoModelForSpeechSeq2Seq.from_pretrained("Kleber/output_dir") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e3d56672071d6487df5cd4ca17e9741f55d9c919da334d6529eaa20c64452df2
- Size of remote file:
- 3.64 kB
- SHA256:
- eabd09a6216c03f5b0f6e770513cc60917650fe53ba59197be81d9a579c945f9
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