Instructions to use Bronsn/whisper-tiny-luganda-final with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Bronsn/whisper-tiny-luganda-final with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Bronsn/whisper-tiny-luganda-final")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Bronsn/whisper-tiny-luganda-final") model = AutoModelForSpeechSeq2Seq.from_pretrained("Bronsn/whisper-tiny-luganda-final") - Notebooks
- Google Colab
- Kaggle
Upload checkpoints/checkpoint-2500/training_args.bin with huggingface_hub
Browse files
checkpoints/checkpoint-2500/training_args.bin
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