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<span class="title">Visual Med-Alpaca: Bridging Modalities in Biomedical Language Models</span> <span class="title">Visual Med-Alpaca: A Parameter-Efficient Biomedical LLM with Visual Capabilities</span>
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<tr><td class="caption"><a href="https://github.com/cambridgeltl/visual-med-alpaca"><b>Visual Med-Alpaca</b></a> is an open-source, multi-modal foundation model specifically for the biomedical domain, built on the <a href="https://research.facebook.com/publications/llama-open-and-efficient-foundation-language-models/">LLaMa-7B</a>. With a few hours of instruct-tuning and plug-and-play visual modules, it was designed to perform a range of tasks, from reading radiological images and answering complex clinical questions, while being easily deployable and replicable with a single gaming GPU. </td></tr> <tr><td class="caption"> Introducing <a href="https://github.com/cambridgeltl/visual-med-alpaca"><strong>Visual Med-Alpaca</strong></a>, an open-source, parameter-efficient biomedical foundation model that can be integrated with medical &quot;visual experts&quot; for multimodal biomedical tasks. Built upon the <a href="https://research.facebook.com/publications/llama-open-and-efficient-foundation-language-models/">LLaMa-7B</a> architecture (<a href="https://arxiv.org/abs/2302.13971">Touvron et al., 2023</a>), this model is trained using an instruction set curated collaboratively by GPT-3.5-Turbo and human experts. Leveraging a few hours of instruction-tuning and the inclusion of plug-and-play visual modules, Visual Med-Alpaca can perform a diverse range of tasks, from interpreting radiological images to addressing complex clinical inquiries. The model can be replicated with ease, necessitating only a single consumer GPU. </td></tr>
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