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  # Introducing MoE-LLaVA-Qwen1.5-1.8B×4-Top2 for Vietnamese
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- We are excited to present MoE-LLaVA-Qwen1.5-1.8B×4-Top2, tailored for the Vietnamese language. This model is part of our ongoing efforts to develop Vision Language Models (VLM) for Vietnamese, a domain that is currently limited and predominantly features larger models (~7B parameters). Our model activates approximately 2.2B parameters per call, significantly reducing the memory footprint, and it can be quantized for local execution.
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  ## Training Dataset
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  # Introducing MoE-LLaVA-Qwen1.5-1.8B×4-Top2 for Vietnamese
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+ We are excited to present MoE-LLaVA-Qwen1.5-1.8B×4-Top2, tailored for the Vietnamese language. This model is part of our ongoing efforts to develop Vision Language Models (VLM) for Vietnamese, a domain that is currently limited and predominantly features larger models (**~7B parameters**). Our model activates approximately **2.2B** 🤗😎 parameters per call, significantly reducing the memory footprint, and it can be quantized for local execution.
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  ## Training Dataset
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