Model
- Name: Whisper Large-v2 Swahili
- Description: Whisper weights for speech-to-text task, fine-tuned and evaluated on normalized data.
- Dataset:
- Train and validation splits for Swahili subsets of Common Voice 11.0.
- Train, validation and test splits for Swahili subsets of Google Fleurs.
- Performance: 30.7 WER
Weights
- Date of release: 12.09.2022
- License: MIT
Usage
To use these weights in HuggingFace's transformers library, you can do the following:
from transformers import WhisperForConditionalGeneration
model = WhisperForConditionalGeneration.from_pretrained("hedronstone/whisper-large-v2-sw")
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