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Model: KOREAson/KO-REAson-KL3_1-8B-0831 Source: Original Platform
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README.md
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---
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library_name: transformers
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tags: []
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---
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# KO-REAson
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**KO-REAson** is a series of Korean-centric reasoning language models developed in collaboration with [OneLineAI](https://onelineai.com/), [KISTI-KONI](https://huggingface.co/KISTI-KONI), [HAE-RAE](https://huggingface.co/HAERAE-HUB) and ORACLE.
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We use the **Language-Mixed Chain-of-Thought (CoT)** approach, which allows the model to alternate between English and Korean during the “Think” stage of reasoning, preserving key Korean terms while leveraging English for logical scaffolding.
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Top-performing models of our series [KO-REAson-AX3_1-7B-0831 (KONI-7B-R-20250831)](https://huggingface.co/KISTI-KONI/KONI-7B-R-20250831) and [KO-REAson-7B-Q2_5-0831](https://huggingface.co/KoReason/KO-REASon-7B-Q2_5-0831) show performance comparable to models trained on closed-source datasets such as Exaone-Deep-7.8B.
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<p align="left">
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<img src="https://cdn-uploads.huggingface.co/production/uploads/60d3e619b8448e1785bbda2a/uqrKdxbQEqAFknYBmuH7Y.png"
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alt="Model Comparison" width="750"/>
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<br>
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<em style="display:inline-block; max-width:750px; text-align:cener; white-space:normal; word-wrap:break-word; line-height:1.5;">
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<b>Left:</b> Average performance (Held-out-Ko) of open models trained on closed or open data;
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our models are highlighted in green.
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</em>
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</p>
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## Model Details
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The **KO-REAson-0831** family comes in six variants based on the base model used.
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| Model (link) | Base | Notes |
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| -------------------------------------------------------------------------------------------- | -------------------- | --------------------------- |
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| [KO-REAson-L3_1-8B-0831](https://huggingface.co/KoReason/KO-REASon-L3_1-8B-0831) | [Llama-3.1-8B](https://huggingface.co/meta-llama/Llama-3.1-8B-Instruct) | `L3_1` → Llama-3.1-8B |
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| [KO-REAson-KL3_1-8B-0831](https://huggingface.co/KOREAson/KO-REAson-KL3_1-8B-0831) | [Koni-Llama-3.1-8B](https://huggingface.co/KISTI-KONI/KONI-Llama3.1-8B-Instruct-20241024) | `KL3_1` → Koni-Llama-3.1-8B; also called [KONI-Llama3.1-8B-R-20250831](https://huggingface.co/KISTI-KONI/KONI-Llama3.1-8B-R-20250831) |
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| [KO-REAson-G3-4B-0831](https://huggingface.co/KoReason/KO-REASon-G3-4B-0831) | [Gemma-3 4B](https://huggingface.co/google/gemma-3-4b-it) | `G3` → Gemma-3-4B |
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| [KO-REAson-AX3_1-7B-0831](https://huggingface.co/KOREAson/KO-REAson-7B-AX3_1-0831) | [A.X.-3.1-Light (≈7B)](https://huggingface.co/skt/A.X-3.1-Light) | `AX3_1` → A.X.-3.1-Light; also called [KONI-7B-R-20250831](https://huggingface.co/KISTI-KONI/KONI-7B-R-20250831) |
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| [KO-REAson-K2505_8B-0831](https://huggingface.co/KoReason/KO-REASon-K2505_8B-0831) | [Kanana-2505 (8B)](https://huggingface.co/kakaocorp/kanana-1.5-8b-instruct-2505) | `K2505` → Kanana-2505 |
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| [KO-REAson-7B-Q2_5-0831](https://huggingface.co/KoReason/KO-REASon-7B-Q2_5-0831) | [Qwen-2.5 (7B)](https://huggingface.co/Qwen/Qwen2.5-7B-Instruct) | `Q2_5` → Qwen-2.5 |
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# Performance
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**Evaluation Datasets**
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The model's performance was evaluated across a total of 11 benchmarks, and the evaluation suite is divided into two parts: (You can check these benchmarks in [HAERAE-HUB/KoSimpleEval](https://huggingface.co/datasets/HAERAE-HUB/KoSimpleEval))
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- **Held-in**: This set of benchmarks is used for routine monitoring of the model's performance during the training and ablation study phases.
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- **Held-out**: This set is used only once to evaluate the final model after all training and ablations are complete.
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This separation is designed to prevent inadvertent overfitting to the benchmarks during the iterative training process and to provide a more accurate measure of the model's generalization capabilities.
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|**Category**|**Held-in**|**Held-out**|
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|---|---|---|
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|**General Knowledge**|KMMLU-Redux|KMMLU-HARD, KMMLU-Pro|
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|**Reasoning**|MCLM|KSM, GPQA, AIME2024, AIME2025|
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|**Korean-specific**|HAE-RAE Bench|CLIcK, KoBALT-700|
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**Comparison with models trained on public datasets**
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<table>
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<thead>
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<tr>
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<th>Models</th>
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<th># Instances</th>
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<th>Methodology</th>
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<th>Held-Out (Ko)</th>
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<th>Held-Out (En)</th>
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<th>Total</th>
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</tr>
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</thead>
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<tbody>
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<tr>
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<th>KO-REASon-AX3_1-7B-0831(KONI-7B-R-20250831; Ours)</th>
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<td>260k</td>
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<td>SFT</td>
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<td><b>44.6</b></td>
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<td>41.2</td>
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<td><u>43.3</u></td>
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</tr>
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<tr>
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<th>KO-REASon-7B-Q2_5-0831(Ours)</th>
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<td>260k</td>
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<td>SFT</td>
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<td><b>45.10</b></td>
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<td>38.75</td>
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<td><u>49.95</u></td>
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</tr>
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<tr>
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<th>KO-REAson-KL3_1-8B-0831(KONI-Llama3.1-8B-R-20250831)</th>
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<td>260k</td>
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<td>SFT</td>
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<td>40.13</td>
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<td>30.57</td>
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<td>43.66</td>
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</tr>
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<tr>
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<td colspan="6" style="text-align:center; font-weight:bold;">Open Recipe (En)</td>
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</tr>
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<tr>
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<th>OpenThinker3-7B</th>
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<td>1.2M</td>
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<td>SFT</td>
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<td>33.6</td>
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<td><b>55.5</b></td>
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<td>41.8</td>
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</tr>
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<tr>
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<th>s1.1-7B</th>
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<td>1k</td>
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<td>SFT</td>
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<td>35.6</td>
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<td>23.4</td>
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<td>31.1</td>
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</tr>
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<tr>
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<th>Llama-3.1-Nemotron-Nano-8B-v1</th>
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<td>>3M</td>
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<td>SFT & RL</td>
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<td>27.0</td>
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<td>44.1</td>
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<td>33.4</td>
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</tr>
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<tr>
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<td colspan="6" style="text-align:center; font-weight:bold;">Open Recipe (Ko)</td>
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</tr>
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<tr>
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<th>Ko-R1-14B</th>
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<td>45k</td>
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<td>SFT</td>
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<td><u>43.7</u></td>
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<td><u>46.3</u></td>
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<td><b>44.7</b></td>
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</tr>
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<tr>
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<th>Ko-R1-7B</th>
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<td>45k</td>
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<td>SFT</td>
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<td>27.3</td>
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<td>36.1</td>
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<td>30.6</td>
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</tr>
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<tr>
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<th>LLaMa-3.1-Ko-Reasoning-8B</th>
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<td>63k</td>
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<td>SFT</td>
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<td>17.7</td>
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<td>7.7</td>
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<td>14.0</td>
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</tr>
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</tbody>
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</table>
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**Held-out benchmark performance**
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<table border="1" cellspacing="0" cellpadding="6">
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<thead>
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<tr>
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<th rowspan="2">Model</th>
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<th rowspan="2">Model Size</th>
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<th colspan="2">General</th>
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<th colspan="4">Reasoning</th>
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<th colspan="2">Korean-Specific</th>
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<th rowspan="2">Average<br>(Held-out)</th>
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<th rowspan="2">Average<br>(Held-out-Ko)</th>
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</tr>
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<tr>
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<th>KMMLU-HARD</th>
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<th>KMMLU-Pro</th>
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<th>KSM</th>
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<th>AIME 2024</th>
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<th>AIME 2025</th>
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<th>GPQA</th>
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<th>CLIcK</th>
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<th>KoBALT-700</th>
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</tr>
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</thead>
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<tbody>
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<tr>
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<td><b>Llama-3.1-Nemotron-Nano-8B</b></td>
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<td>8.03</td><td>21.47</td><td>22.89</td><td>47.06</td><td>56.67</td><td>43.33</td><td>32.32</td><td>34.54</td><td>9.29</td><td>33.45</td><td>27.05</td>
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</tr>
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<tr>
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<td><b>Llama-3.1-Korean-Reasoning-8B-Instruct</b></td>
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<td>8.03</td><td>14.91</td><td>21.72</td><td>6.09</td><td>0.00</td><td>0.00</td><td>23.23</td><td>39.65</td><td>6.14</td><td>13.97</td><td>17.70</td>
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</tr>
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<tr>
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<td><b>EXAONE-Deep-7.8B</b></td>
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<td>7.82</td><td><u>40.96</u></td><td>37.35</td><td><b>70.80</b></td><td><b>70.00</b></td><td><b>63.33</b></td><td><b>64.65</b></td><td>54.24</td><td>18.86</td><td><b>52.52</b></td><td>44.44</td>
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</tr>
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<tr>
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<td><b>DeepSeek-R1-Distill-Qwen-7B</b></td>
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<td>7.62</td><td>0.00</td><td>23.00</td><td>56.09</td><td>60.00</td><td>40.00</td><td>43.43</td><td>0.00</td><td>8.29</td><td>28.85</td><td>17.48</td>
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</tr>
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<tr>
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<td><b>DeepSeek-R1-Distill-Llama-8B</b></td>
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<td>8.03</td><td>23.22</td><td>26.26</td><td>29.97</td><td>33.33</td><td>20.00</td><td><U>46.46</u></td><td>39.05</td><td>13.29</td><td>28.95</td><td>26.36</td>
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</tr>
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<tr>
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<td><b>s1.1-7B</b></td>
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<td>7.62</td><td>31.16</td><td><u>37.70</u></td><td>30.60</td><td>16.67</td><td>23.33</td><td>30.30</td><td><u>56.84</u></td><td><u>21.86</u></td><td>31.06</td><td>35.63</td>
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</tr>
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<tr>
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<td><b>OpenThinker3-7B</b></td>
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<td>7.62</td><td>30.31</td><td>26.26</td><td><u>63.59</u></td><td><u>66.67</u></td><td><u>53.33</u></td><td><u>46.46</u></td><td>47.69</td><td>10.14</td><td>35.63</td><td>30.60</td>
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</tr>
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<tr>
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<td><b>Ko-R1-7B</b></td>
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<td>7.61</td><td>28.46</td><td>19.31</td><td>51.61</td><td>46.67</td><td>33.33</td><td>28.28</td><td>32.48</td><td>4.71</td><td>30.61</td><td>27.31</td>
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</tr>
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<tr>
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<td><b>KO-REAson-KL3_1-8B-0831(KONI-Llama3.1-8B-R-20250831)</b></td>
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<td>8.03</td><td>44.64</td><td>40.08</td><td>37.96</td><td>23.33</td><td>30.00</td><td>38.38</td><td>56.39</td><td>21.57</td><td>30.57</td><td>40.13</td>
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</tr>
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<tr>
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<td><b>KO-REASon-AX3_1-7B-0831 (KONI-7B-R-20250831)</b></td>
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<td>7.26</td><td>45.57</td><td>38.13</td><td>52.80</td><td>53.33</td><td>33.33</td><td>36.87</td><td><b>62.86</b></td><td>23.43</td><td><u>43.29</u></td><td><u>44.56</u></td>
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</tr>
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<tr>
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<td><b>KO-REASon-7B-Q2_5-0831</b></td>
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<td>7.26</td><td><b>46.81</b></td><td><b>44.93</b></td><td>48.11</td><td>43.33</td><td>30.00</td><td>42.93</td><td>60.65</td><td><b>25.00</b></td><td>42.72</td><td><b>45.10</b></td>
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</tr>
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</tbody>
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</table>
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## Citation
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```
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The paper will be released soon!
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```
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## Contact
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For any questions contact us via the following email :)
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```
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spthsrbwls123@yonsei.ac.kr
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```
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## Acknowlegments
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This research was supported by the Korea Institute of Science and Technology Information (KISTI) (No.(KISTI) K25L1M1C1), aimed at developing KONI (KISTI Open Neural Intelligence), a large language model specialized in science and technology.
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114
chat_template.jinja
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chat_template.jinja
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{{- bos_token }}
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{%- if custom_tools is defined %}
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{%- set tools = custom_tools %}
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{%- endif %}
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{%- if not tools_in_user_message is defined %}
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{%- set tools_in_user_message = true %}
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{%- endif %}
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{%- if not date_string is defined %}
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{%- set date_string = "27 Aug 2024" %}
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{%- endif %}
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{%- if not tools is defined %}
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{%- set tools = none %}
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{%- endif %}
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{#- This block extracts the system message, so we can slot it into the right place. #}
|
||||
{%- if messages[0]['role'] == 'system' %}
|
||||
{%- set system_message = messages[0]['content']|trim %}
|
||||
{%- set messages = messages[1:] %}
|
||||
{%- else %}
|
||||
{%- set system_message = "" %}
|
||||
{%- endif %}
|
||||
|
||||
{#- System message + builtin tools #}
|
||||
{{- "<|start_header_id|>system<|end_header_id|>\n\n" }}
|
||||
{%- if builtin_tools is defined or tools is not none %}
|
||||
{{- "Environment: ipython\n" }}
|
||||
{%- endif %}
|
||||
{%- if builtin_tools is defined %}
|
||||
{{- "Tools: " + builtin_tools | reject('equalto', 'code_interpreter') | join(", ") + "\n\n"}}
|
||||
{%- endif %}
|
||||
{{- "You are KONI, an AI assistant trained based on LlaMA3.1 and created by KISTI to be helpful and honest. Your knowledge spans a wide range of topics, allowing you to engage in substantive conversations and provide analysis on complex subjects. Below is an instruction that describes a task. Write a response that appropriately completes the request. If you don't know the answer, just say that you don't know.\n" }}
|
||||
{{- "Cutting Knowledge Date: July 2024\n" }}
|
||||
{{- "Today Date: " + date_string + "\n\n" }}
|
||||
{%- if tools is not none and not tools_in_user_message %}
|
||||
{{- "You have access to the following functions. To call a function, please respond with JSON for a function call." }}
|
||||
{{- 'Respond in the format {"name": function name, "parameters": dictionary of argument name and its value}.' }}
|
||||
{{- "Do not use variables.\n\n" }}
|
||||
{%- for t in tools %}
|
||||
{{- t | tojson(indent=4) }}
|
||||
{{- "\n\n" }}
|
||||
{%- endfor %}
|
||||
{%- endif %}
|
||||
{{- system_message }}
|
||||
{{- "<|eot_id|>" }}
|
||||
|
||||
{#- Custom tools are passed in a user message with some extra guidance #}
|
||||
{%- if tools_in_user_message and not tools is none %}
|
||||
{#- Extract the first user message so we can plug it in here #}
|
||||
{%- if messages | length != 0 %}
|
||||
{%- set first_user_message = messages[0]['content']|trim %}
|
||||
{%- set messages = messages[1:] %}
|
||||
{%- else %}
|
||||
{{- raise_exception("Cannot put tools in the first user message when there's no first user message!") }}
|
||||
{%- endif %}
|
||||
{{- '<|start_header_id|>user<|end_header_id|>\n\n' -}}
|
||||
{{- "Given the following functions, please respond with a JSON for a function call " }}
|
||||
{{- "with its proper arguments that best answers the given prompt.\n\n" }}
|
||||
{{- 'Respond in the format {"name": function name, "parameters": dictionary of argument name and its value}.' }}
|
||||
{{- "Do not use variables.\n\n" }}
|
||||
{%- for t in tools %}
|
||||
{{- t | tojson(indent=4) }}
|
||||
{{- "\n\n" }}
|
||||
{%- endfor %}
|
||||
{{- first_user_message + "<|eot_id|>"}}
|
||||
{%- endif %}
|
||||
|
||||
{%- for message in messages %}
|
||||
{%- if not (message.role == 'ipython' or message.role == 'tool' or 'tool_calls' in message) %}
|
||||
{%- if (message.role == 'assistant') %}
|
||||
{{- '<|start_header_id|>' + 'KONI' + '<|end_header_id|>\n\n'+ message['content'] | trim + '<|eot_id|>' }}
|
||||
{%- else %}
|
||||
{{- '<|start_header_id|>' + message['role'] + '<|end_header_id|>\n\n'+ message['content'] | trim + '<|eot_id|>' }}
|
||||
{%- endif %}
|
||||
{%- elif 'tool_calls' in message %}
|
||||
{%- if not message.tool_calls|length == 1 %}
|
||||
{{- raise_exception("This model only supports single tool-calls at once!") }}
|
||||
{%- endif %}
|
||||
{%- set tool_call = message.tool_calls[0].function %}
|
||||
{%- if builtin_tools is defined and tool_call.name in builtin_tools %}
|
||||
{{- '<|start_header_id|>KONI<|end_header_id|>\n\n' -}}
|
||||
{{- "<|python_tag|>" + tool_call.name + ".call(" }}
|
||||
{%- for arg_name, arg_val in tool_call.arguments | items %}
|
||||
{{- arg_name + '="' + arg_val + '"' }}
|
||||
{%- if not loop.last %}
|
||||
{{- ", " }}
|
||||
{%- endif %}
|
||||
{%- endfor %}
|
||||
{{- ")" }}
|
||||
{%- else %}
|
||||
{{- '<|start_header_id|>KONI<|end_header_id|>\n\n' -}}
|
||||
{{- '{"name": "' + tool_call.name + '", ' }}
|
||||
{{- '"parameters": ' }}
|
||||
{{- tool_call.arguments | tojson }}
|
||||
{{- "}" }}
|
||||
{%- endif %}
|
||||
{%- if builtin_tools is defined %}
|
||||
{#- This means we're in ipython mode #}
|
||||
{{- "<|eom_id|>" }}
|
||||
{%- else %}
|
||||
{{- "<|eot_id|>" }}
|
||||
{%- endif %}
|
||||
{%- elif message.role == "tool" or message.role == "ipython" %}
|
||||
{{- "<|start_header_id|>ipython<|end_header_id|>\n\n" }}
|
||||
{%- if message.content is mapping or message.content is iterable %}
|
||||
{{- message.content | tojson }}
|
||||
{%- else %}
|
||||
{{- message.content }}
|
||||
{%- endif %}
|
||||
{{- "<|eot_id|>" }}
|
||||
{%- endif %}
|
||||
{%- endfor %}
|
||||
{%- if add_generation_prompt %}
|
||||
{{- '<|start_header_id|>KONI<|end_header_id|>\n\n' }}
|
||||
{%- endif %}
|
||||
35
config.json
Normal file
35
config.json
Normal file
@@ -0,0 +1,35 @@
|
||||
{
|
||||
"architectures": [
|
||||
"LlamaForCausalLM"
|
||||
],
|
||||
"attention_bias": false,
|
||||
"attention_dropout": 0.0,
|
||||
"bos_token_id": 128000,
|
||||
"eos_token_id": 128001,
|
||||
"head_dim": 128,
|
||||
"hidden_act": "silu",
|
||||
"hidden_size": 4096,
|
||||
"initializer_range": 0.02,
|
||||
"intermediate_size": 14336,
|
||||
"max_position_embeddings": 131072,
|
||||
"mlp_bias": false,
|
||||
"model_type": "llama",
|
||||
"num_attention_heads": 32,
|
||||
"num_hidden_layers": 32,
|
||||
"num_key_value_heads": 8,
|
||||
"pretraining_tp": 1,
|
||||
"rms_norm_eps": 1e-05,
|
||||
"rope_scaling": {
|
||||
"factor": 8.0,
|
||||
"high_freq_factor": 4.0,
|
||||
"low_freq_factor": 1.0,
|
||||
"original_max_position_embeddings": 8192,
|
||||
"rope_type": "llama3"
|
||||
},
|
||||
"rope_theta": 500000.0,
|
||||
"tie_word_embeddings": false,
|
||||
"torch_dtype": "float32",
|
||||
"transformers_version": "4.55.4",
|
||||
"use_cache": true,
|
||||
"vocab_size": 128256
|
||||
}
|
||||
1
configuration.json
Normal file
1
configuration.json
Normal file
@@ -0,0 +1 @@
|
||||
{"framework": "pytorch", "task": "text-generation", "allow_remote": true}
|
||||
6
generation_config.json
Normal file
6
generation_config.json
Normal file
@@ -0,0 +1,6 @@
|
||||
{
|
||||
"_from_model_config": true,
|
||||
"bos_token_id": 128000,
|
||||
"eos_token_id": 128001,
|
||||
"transformers_version": "4.55.4"
|
||||
}
|
||||
3
model-00001-of-00007.safetensors
Normal file
3
model-00001-of-00007.safetensors
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
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||||
oid sha256:726490927ea06607b0a1a13994b0662fdc883a3dadad212061465818f9e033a0
|
||||
size 4886466168
|
||||
3
model-00002-of-00007.safetensors
Normal file
3
model-00002-of-00007.safetensors
Normal file
@@ -0,0 +1,3 @@
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||||
version https://git-lfs.github.com/spec/v1
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oid sha256:8d3e6917f461fde3a97ccaaa578b474f07f70ff6c58a342261e48baa826362a5
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size 4832007448
|
||||
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Normal file
3
model-00003-of-00007.safetensors
Normal file
@@ -0,0 +1,3 @@
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||||
version https://git-lfs.github.com/spec/v1
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oid sha256:3ce97c72935073ab6a7c50bc2b320155df80f46251ef8bf088a30bc37a92a091
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size 4999813112
|
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3
model-00004-of-00007.safetensors
Normal file
3
model-00004-of-00007.safetensors
Normal file
@@ -0,0 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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oid sha256:c5965898aa4f442cad9543fe58e3d8334f11f5e35caade889e3daa92eb6abfd0
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size 4999813128
|
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Normal file
3
model-00005-of-00007.safetensors
Normal file
@@ -0,0 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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oid sha256:c0a1362a790ac81a63a2b91a81b1d7d88c7efc747c9df26e5c5bf9ed4493dda4
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size 4832007496
|
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model-00006-of-00007.safetensors
Normal file
3
model-00006-of-00007.safetensors
Normal file
@@ -0,0 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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oid sha256:6f11514d1a474e726b76f17b83a29a61a21b3e49527288daaf264ee4d35b0fa6
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size 4999813120
|
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Normal file
3
model-00007-of-00007.safetensors
Normal file
@@ -0,0 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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oid sha256:bae7dbb1f8bfe3c3229babb7c2747d5f0d27003612a3328ab95e627d964a0f34
|
||||
size 2571158184
|
||||
299
model.safetensors.index.json
Normal file
299
model.safetensors.index.json
Normal file
@@ -0,0 +1,299 @@
|
||||
{
|
||||
"metadata": {
|
||||
"total_parameters": 8030261248,
|
||||
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|
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|
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"model.layers.9.self_attn.o_proj.weight": "model-00003-of-00007.safetensors",
|
||||
"model.layers.9.self_attn.q_proj.weight": "model-00003-of-00007.safetensors",
|
||||
"model.layers.9.self_attn.v_proj.weight": "model-00003-of-00007.safetensors",
|
||||
"model.norm.weight": "model-00007-of-00007.safetensors"
|
||||
}
|
||||
}
|
||||
23
special_tokens_map.json
Normal file
23
special_tokens_map.json
Normal file
@@ -0,0 +1,23 @@
|
||||
{
|
||||
"bos_token": {
|
||||
"content": "<|begin_of_text|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
},
|
||||
"eos_token": {
|
||||
"content": "<|eot_id|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
},
|
||||
"pad_token": {
|
||||
"content": "<|finetune_right_pad_id|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
}
|
||||
}
|
||||
BIN
tokenizer.json
(Stored with Git LFS)
Normal file
BIN
tokenizer.json
(Stored with Git LFS)
Normal file
Binary file not shown.
2067
tokenizer_config.json
Normal file
2067
tokenizer_config.json
Normal file
File diff suppressed because it is too large
Load Diff
Reference in New Issue
Block a user