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README.md

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 The model is optimized for fast inference, with aggressive input downsampling and variable chunk sizing unlike the competing models, this enables our Saga model to achieve state-of-the-art performance, while being significantly more efficient.
 
-The model was trained <18 hours on an nvidia B200, with the use of the [`CoRal dataset`](https://huggingface.co/CoRal-project/datasets) family, courtesy of the [`Danish Innovation fund`](https://innovationsfonden.dk/da) and the [`Alexandra Institute`](https://alexandra.dk)
+The model was trained on an nvidia B200, with the use of the [`CoRal dataset`](https://huggingface.co/CoRal-project/datasets) family, courtesy of the [`Danish Innovation fund`](https://innovationsfonden.dk/da) and the [`Alexandra Institute`](https://alexandra.dk)
 
 This repository is intended for Danish transcription only. The underlying Qwen3-ASR base model is multilingual, but this finetuned checkpoint is Danish-focused and the model has unlearned most of its multilingual capabilities.