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🌟 MG-LLaVA - multimodal LLM with advanced capabilities for working with visual information

Just recently, the guys from Shanghai University rolled out MG-LLaVA - MLLM, which expands the capabilities of processing visual information through the use of additional components: special components that are responsible for working with low and high resolution.

MG-LLaVA integrates an additional high-resolution visual encoder to capture fine details, which are then combined with underlying visual features using the Conv-Gate network.

Trained exclusively on publicly available multimodal data, MG-LLaVA achieves excellent results.

🟡 MG-LLaVA page
🖥 GitHub

@Machine_learn



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🌟 MG-LLaVA - multimodal LLM with advanced capabilities for working with visual information

Just recently, the guys from Shanghai University rolled out MG-LLaVA - MLLM, which expands the capabilities of processing visual information through the use of additional components: special components that are responsible for working with low and high resolution.

MG-LLaVA integrates an additional high-resolution visual encoder to capture fine details, which are then combined with underlying visual features using the Conv-Gate network.

Trained exclusively on publicly available multimodal data, MG-LLaVA achieves excellent results.

🟡 MG-LLaVA page
🖥 GitHub

@Machine_learn

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