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Merge branch 'main' of https://github.com/OpenBMB/OmniLMM

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yiranyyu
2024-02-02 12:54:00 +08:00
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README.md
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- 🔥 **Strong Performance.** - 🔥 **Strong Performance.**
OmniLMM-12B achieves **leading performance** among models with comparable sizes, surpassing established LMMs on multiple benchmarks (including MME, MMBench, SEED-Bench, etc). OmniLMM-12B achieves **leading performance** among models with comparable sizes, surpassing established LMMs on multiple benchmarks (including MME, MMBench, SEED-Bench, etc). The model also endows rich multi-modal world knowledge.
- 🏆 **Trustworthy Behavior.** - 🏆 **Trustworthy Behavior.**

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- 🏆 **可信行为。** - 🏆 **可信行为。**
LMMs 的幻觉问题备受关注，模型经常生成和图像中的事实不符的文本（例如，信誓旦旦地描述图片中并不存在的物体）。OmniLMM-12B是 **第一个通过多模态 RLHF 对齐的最新开源 LMM 来实现可信行为**（通过我们最近提出的 [RLHF-V](https://rlhf-v.github.io/) 技术）。该模型在 [MMHal-Bench](https://huggingface.co/datasets/Shengcao1006/MMHal-Bench) 幻觉评测基准上位列开源模型中**第一**，并在 [Object HalBench](https://arxiv.org/abs/2312.00849) 中**超过了 GPT-4V**。 LMMs 的幻觉问题备受关注，模型经常生成和图像中的事实不符的文本（例如，确信地描述图片中并不存在的物体）。OmniLMM-12B是 **第一个通过多模态 RLHF 对齐的综合能力优秀的开源多模态大模型**（通过我们最近提出的 [RLHF-V](https://rlhf-v.github.io/) 技术）。该模型在 [MMHal-Bench](https://huggingface.co/datasets/Shengcao1006/MMHal-Bench) 幻觉评测基准上位列开源模型中**第一**，并在 [Object HalBench](https://arxiv.org/abs/2312.00849) 中**超过了 GPT-4V**。
- 🕹 **实时多模态交互。** - 🕹 **实时多模态交互。**