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README.md
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README.md
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[中文文档](./README_zh.md)
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## Contents
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- [Contents](#contents)
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- [OmniLMM-12B](#omnilmm-12b)
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- [Evaluation](#evaluation)
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- [Examples](#examples)
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- [OmniLMM-3B](#omnilmm-3b)
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- [Evaluation](#evaluation-1)
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- [Examples](#examples-1)
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- [Demo](#demo)
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- [Install](#install)
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- [Inference](#inference)
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- [Model Zoo](#model-zoo)
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- [Model Zoo](#model-zoo)
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- [Multi-turn Conversation](#multi-turn-conversation)
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- [✅ TODO](#-todo)
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- [Model License](#model-license)
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- [Statement](#statement)
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- [🏫 Institutions](#-institutions)
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## OmniLMM-12B
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**OmniLMM-12B** is the most capable version. The model is built based on EVA02-5B and Zephyr-7B-β, connected with a perceiver resampler layer, and trained on multimodal data in a curriculum fashion. The model has three notable features:
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@@ -181,79 +191,118 @@ We combine the OmniLMM-12B and GPT-3.5 (text-only) into a **real-time multimodal
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OmniLMM-3B is **the first edge-deployable LMM supporting bilingual multimodal interaction in English and Chinese**. This is achieved by generalizing multimodal capabilities across languages, a technique from our ICLR 2024 spotlight [paper](https://arxiv.org/abs/2308.12038).
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### Evaluation
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<div align="center">
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<img src=assets/eval_radar.png width=50% />
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</div>
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<details>
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<summary>Click to view results on MME, MMBench, MMMU, MMBench, MMHal-Bench, Object HalBench, SeedBench, LLaVA Bench W. </summary>
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<table style="margin: 0px auto;">
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<table>
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<thead>
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<tr>
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<th align="left">Model</th>
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<th>Size</th>
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<th>MME</th>
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<th nowrap="nowrap" >MMB dev (en)</th>
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<th nowrap="nowrap" >MMB dev (zh)</th>
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<th nowrap="nowrap">MMB dev (en)</th>
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<th nowrap="nowrap" >MMMU val</th>
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<th nowrap="nowrap" >CMMMU val</th>
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<th nowrap="nowrap" >MMHal-Bench</th>
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<th nowrap="nowrap" >Object HalBench</th>
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<th nowrap="nowrap" >SeedBench-I</th>
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<th>MathVista</th>
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<th nowrap="nowrap" >LLaVA Bench W</th>
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</tr>
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</thead>
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<tbody align="center">
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<tr>
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<td align="left">LLaVA-Phi</td>
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<td align="right">3B</td>
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<td>1335</td>
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<td>59.8</td>
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<td>- </td>
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<td>- </td>
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<td>- </td>
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<td align="left">GPT-4V†</td>
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<td>-</td>
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<td>1409</td>
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<td>75.1 </td>
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<td>56.8</td>
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<td>3.53 / 70.8</td>
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<td>86.4 / 92.7</td>
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<td>71.6 </td>
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<td>47.8 </td>
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<td>93.1 </td>
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</tr>
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<tr>
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<td nowrap="nowrap" align="left">MobileVLM</td>
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<td align="right">3B</td>
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<td>1289</td>
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<td>59.6</td>
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<td>- </td>
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<td nowrap="nowrap" align="left">Qwen-VL-Plus†</td>
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<td>-</td>
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<td>1681</td>
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<td>66.2 </td>
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<td>45.2</td>
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<td>- </td>
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<td>- </td>
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<td>65.7 </td>
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<td>36.0 </td>
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<td>73.7 </td>
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</tr>
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<tr>
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<td nowrap="nowrap" align="left" >Imp-v1</td>
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<td align="right">3B</td>
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<td>1434</td>
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<td>66.5</td>
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<td>- </td>
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<td align="left">Yi-VL 6B</td>
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<td align="right">6.7B </td>
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<td>- </td>
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<td>68.2 </td>
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<td>39.1 </td>
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<td>- </td>
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<td>- </td>
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<td>66.1 </td>
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<td>28.0 </td>
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<td>39.9 </td>
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</tr>
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<tr>
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<td align="left" >Qwen-VL-Chat</td>
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<td align="right" >9.6B</td>
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<td>1487</td>
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<td nowrap="nowrap" align="left" >Qwen-VL-Chat</td>
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<td align="right">9.6B</td>
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<td>1488</td>
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<td>60.6 </td>
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<td>56.7 </td>
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<td>35.9 </td>
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<td>30.7 </td>
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<td>35.9</td>
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<td>2.93 / 59.4</td>
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<td>56.2 / 80.0</td>
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<td>64.8 </td>
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<td>33.8 </td>
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<td>67.7 </td>
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</tr>
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<tr>
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<td nowrap="nowrap" align="left" >CogVLM</td>
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<td align="right">17.4B </td>
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<td>1438 </td>
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<td align="left" >CogVLM</td>
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<td align="right">17.4B</td>
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<td>1438</td>
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<td>63.7 </td>
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<td>53.8 </td>
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<td>32.1 </td>
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<td>- </td>
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<td>2.68 / 52.1 </td>
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<td>73.6 / 87.4 </td>
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<td>68.8 </td>
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<td>34.7 </td>
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<td>73.9 </td>
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</tr>
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<tr>
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<td nowrap="nowrap" align="left" ><b>OmniLMM-3B</b></td>
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<td align="right">3B </td>
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<td>1452 </td>
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<td>67.3 </td>
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<td>61.9 </td>
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<td>34.7 </td>
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<td>32.1 </td>
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<td align="left" >LLaVA 1.5</td>
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<td align="right">13.6B </td>
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<td>1531 </td>
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<td>68.2 </td>
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<td>36.4 </td>
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<td>2.71 / 51.0 </td>
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<td>53.7 / 77.4 </td>
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<td>68.1 </td>
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<td>26.4 </td>
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<td>64.6 </td>
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</tr>
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<tr>
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<td nowrap="nowrap" align="left" ><b>OmniLMM-12B</b></td>
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<td align="right">11.6B </td>
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<td>1637 </td>
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<td>71.6 </td>
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<td>40.7 </td>
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<td>3.45 / 68.8 </td>
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<td>90.3 / 95.5 </td>
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<td>71.1 </td>
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<td>34.9 </td>
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<td>72.0 </td>
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</tr>
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</tbody>
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</table>
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<small>†: Proprietary models</small>
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</details>
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</div>
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