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README.md
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# π₯ SPHINX: A Mixer of Tasks, Domains, and Embeddings
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Official implementation of ['SPHINX: A Mixer of Tasks, Domains, and Embeddings Advances Multi-modal Large Language Models']().
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Try out our [web demo π](http://imagebind-llm.opengvlab.com/) here!
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- **Domain Mix.** For data from real-world and synthetic domains, we mix the weights of two domain-specific models for complementarity.
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<p align="center">
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## Demo
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Via our proposed three-fold mixer, $\color{goldenrod}{SPHINX}$ exhibits superior multi-modal understanding and reasoning powers.
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<p align="center"> <img src="figs/1.png"/ width="70%"> <br>
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</p>
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<p align="center"> <img src="figs/2.png"/ width="70%"> <br>
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</p>
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<p align="center"> <img src="figs/3.png"/ width="70%"> <br>
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<p align="center"> <img src="figs/4.png"/ width="50%"> <br>
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<p align="center"> <img src="figs/5.png"/ width="60%"> <br>
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</p>
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## Inference
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This section provides a step-by-step guide for hosting a local SPHINX demo. If you're already familiar with the LLAMA2-Accessory toolkit, note that hosting a SPHINX demo follows the same pipeline as hosting demos for the other models supported by LLAMA2-Accessory.
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---
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# π₯ SPHINX: A Mixer of Tasks, Domains, and Embeddings
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Official implementation of ['SPHINX: A Mixer of Tasks, Domains, and Embeddings Advances Multi-modal Large Language Models'](https://github.com/Alpha-VLLM/LLaMA2-Accessory/tree/main/SPHINX).
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Try out our [web demo π](http://imagebind-llm.opengvlab.com/) here!
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- **Domain Mix.** For data from real-world and synthetic domains, we mix the weights of two domain-specific models for complementarity.
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<p align="center">
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<img src="https://github.com/Alpha-VLLM/LLaMA2-Accessory/blob/main/SPHINX/figs/pipeline.png"/ width="90%"> <br>
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</p>
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<p align="center">
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<img src="https://github.com/Alpha-VLLM/LLaMA2-Accessory/blob/main/SPHINX/figs/pipeline2.png"/ width="90%"> <br>
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</p>
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## Inference
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This section provides a step-by-step guide for hosting a local SPHINX demo. If you're already familiar with the LLAMA2-Accessory toolkit, note that hosting a SPHINX demo follows the same pipeline as hosting demos for the other models supported by LLAMA2-Accessory.
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