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The model uses a pre-trained [Llama3.1-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3.1-8B) backbone as well as the encoder part of [whisper-large-v3-turbo](https://huggingface.co/openai/whisper-large-v3-turbo).
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We use a knowledge-distillation loss where Ultravox is trying to match the logits of the text-based Llama backbone.
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The model uses a pre-trained [Llama3.1-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3.1-8B) backbone as well as the encoder part of [whisper-large-v3-turbo](https://huggingface.co/openai/whisper-large-v3-turbo).
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The multi-modal adapter is trained, the Whisper encoder is fine-tuned, while the Llama model is kept frozen.
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We use a knowledge-distillation loss where Ultravox is trying to match the logits of the text-based Llama backbone.
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