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Browse files- .gitattributes +4 -0
- LICENSE +51 -0
- README.md +509 -3
- assets/A.X_logo.png +0 -0
- assets/A.X_logo_ko_4x3.png +3 -0
- generation_config.json +9 -0
- merges.txt +0 -0
- model-00001-of-00030.safetensors +3 -0
- model-00002-of-00030.safetensors +3 -0
- model-00003-of-00030.safetensors +3 -0
- model-00004-of-00030.safetensors +3 -0
- model-00005-of-00030.safetensors +3 -0
- model-00006-of-00030.safetensors +3 -0
- model-00007-of-00030.safetensors +3 -0
- model-00008-of-00030.safetensors +3 -0
- model-00009-of-00030.safetensors +3 -0
- model-00010-of-00030.safetensors +3 -0
- model-00011-of-00030.safetensors +3 -0
- model-00012-of-00030.safetensors +3 -0
- model-00013-of-00030.safetensors +3 -0
- model-00014-of-00030.safetensors +3 -0
- model-00015-of-00030.safetensors +3 -0
- model-00016-of-00030.safetensors +3 -0
- model-00017-of-00030.safetensors +3 -0
- model-00018-of-00030.safetensors +3 -0
- model-00019-of-00030.safetensors +3 -0
- model-00020-of-00030.safetensors +3 -0
- model-00021-of-00030.safetensors +3 -0
- model-00022-of-00030.safetensors +3 -0
- model-00023-of-00030.safetensors +3 -0
- model-00024-of-00030.safetensors +3 -0
- model-00025-of-00030.safetensors +3 -0
- model-00026-of-00030.safetensors +3 -0
- model-00027-of-00030.safetensors +3 -0
- model-00028-of-00030.safetensors +3 -0
- model-00029-of-00030.safetensors +3 -0
- model-00030-of-00030.safetensors +3 -0
- model.safetensors.index.json +970 -0
- pytorch_model.bin.index.json +970 -0
- special_tokens_map.json +90 -0
- tokenizer_config.json +391 -0
- vocab.json +0 -0
.gitattributes
CHANGED
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@@ -33,3 +33,7 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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| 33 |
*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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assets/A.X_logo_ko.jpg filter=lfs diff=lfs merge=lfs -text
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A.X_logo_ko.png filter=lfs diff=lfs merge=lfs -text
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assets/A.X_logo_ko.png filter=lfs diff=lfs merge=lfs -text
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assets/A.X_logo_ko_4x3.png filter=lfs diff=lfs merge=lfs -text
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LICENSE
ADDED
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@@ -0,0 +1,51 @@
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| 1 |
+
Qwen LICENSE AGREEMENT
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| 3 |
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Qwen LICENSE AGREEMENT Release Date: September 19, 2024
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By clicking to agree or by using or distributing any portion or element of the Qwen Materials, you will be deemed to have recognized and accepted the content of this Agreement, which is effective immediately.
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1. Definitions
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a. This Qwen LICENSE AGREEMENT (this "Agreement") shall mean the terms and conditions for use, reproduction, distribution and modification of the Materials as defined by this Agreement.
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b. "We" (or "Us") shall mean Alibaba Cloud.
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c. "You" (or "Your") shall mean a natural person or legal entity exercising the rights granted by this Agreement and/or using the Materials for any purpose and in any field of use.
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d. "Third Parties" shall mean individuals or legal entities that are not under common control with us or you.
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e. "Qwen" shall mean the large language models, and software and algorithms, consisting of trained model weights, parameters (including optimizer states), machine-learning model code, inference-enabling code, training-enabling code, fine-tuning enabling code and other elements of the foregoing distributed by us.
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f. "Materials" shall mean, collectively, Alibaba Cloud's proprietary Qwen and Documentation (and any portion thereof) made available under this Agreement.
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g. "Source" form shall mean the preferred form for making modifications, including but not limited to model source code, documentation source, and configuration files.
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h. "Object" form shall mean any form resulting from mechanical transformation or translation of a Source form, including but not limited to compiled object code, generated documentation, and conversions to other media types.
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2. Grant of Rights
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You are granted a non-exclusive, worldwide, non-transferable and royalty-free limited license under Alibaba Cloud's intellectual property or other rights owned by us embodied in the Materials to use, reproduce, distribute, copy, create derivative works of, and make modifications to the Materials.
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3. Redistribution
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You may distribute copies or make the Materials, or derivative works thereof, available as part of a product or service that contains any of them, with or without modifications, and in Source or Object form, provided that you meet the following conditions:
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a. You shall give any other recipients of the Materials or derivative works a copy of this Agreement;
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b. You shall cause any modified files to carry prominent notices stating that you changed the files;
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c. You shall retain in all copies of the Materials that you distribute the following attribution notices within a "Notice" text file distributed as a part of such copies: "Qwen is licensed under the Qwen LICENSE AGREEMENT, Copyright (c) Alibaba Cloud. All Rights Reserved."; and
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d. You may add your own copyright statement to your modifications and may provide additional or different license terms and conditions for use, reproduction, or distribution of your modifications, or for any such derivative works as a whole, provided your use, reproduction, and distribution of the work otherwise complies with the terms and conditions of this Agreement.
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4. Restrictions
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If you are commercially using the Materials, and your product or service has more than 100 million monthly active users, you shall request a license from us. You cannot exercise your rights under this Agreement without our express authorization.
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5. Rules of use
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a. The Materials may be subject to export controls or restrictions in China, the United States or other countries or regions. You shall comply with applicable laws and regulations in your use of the Materials.
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b. If you use the Materials or any outputs or results therefrom to create, train, fine-tune, or improve an AI model that is distributed or made available, you shall prominently display “Built with Qwen” or “Improved using Qwen” in the related product documentation.
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6. Intellectual Property
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a. We retain ownership of all intellectual property rights in and to the Materials and derivatives made by or for us. Conditioned upon compliance with the terms and conditions of this Agreement, with respect to any derivative works and modifications of the Materials that are made by you, you are and will be the owner of such derivative works and modifications.
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b. No trademark license is granted to use the trade names, trademarks, service marks, or product names of us, except as required to fulfill notice requirements under this Agreement or as required for reasonable and customary use in describing and redistributing the Materials.
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c. If you commence a lawsuit or other proceedings (including a cross-claim or counterclaim in a lawsuit) against us or any entity alleging that the Materials or any output therefrom, or any part of the foregoing, infringe any intellectual property or other right owned or licensable by you, then all licenses granted to you under this Agreement shall terminate as of the date such lawsuit or other proceeding is commenced or brought.
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7. Disclaimer of Warranty and Limitation of Liability
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a. We are not obligated to support, update, provide training for, or develop any further version of the Qwen Materials or to grant any license thereto.
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b. THE MATERIALS ARE PROVIDED "AS IS" WITHOUT ANY EXPRESS OR IMPLIED WARRANTY OF ANY KIND INCLUDING WARRANTIES OF MERCHANTABILITY, NONINFRINGEMENT, OR FITNESS FOR A PARTICULAR PURPOSE. WE MAKE NO WARRANTY AND ASSUME NO RESPONSIBILITY FOR THE SAFETY OR STABILITY OF THE MATERIALS AND ANY OUTPUT THEREFROM.
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c. IN NO EVENT SHALL WE BE LIABLE TO YOU FOR ANY DAMAGES, INCLUDING, BUT NOT LIMITED TO ANY DIRECT, OR INDIRECT, SPECIAL OR CONSEQUENTIAL DAMAGES ARISING FROM YOUR USE OR INABILITY TO USE THE MATERIALS OR ANY OUTPUT OF IT, NO MATTER HOW IT’S CAUSED.
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d. You will defend, indemnify and hold harmless us from and against any claim by any third party arising out of or related to your use or distribution of the Materials.
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8. Survival and Termination.
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a. The term of this Agreement shall commence upon your acceptance of this Agreement or access to the Materials and will continue in full force and effect until terminated in accordance with the terms and conditions herein.
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b. We may terminate this Agreement if you breach any of the terms or conditions of this Agreement. Upon termination of this Agreement, you must delete and cease use of the Materials. Sections 7 and 9 shall survive the termination of this Agreement.
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9. Governing Law and Jurisdiction.
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a. This Agreement and any dispute arising out of or relating to it will be governed by the laws of China, without regard to conflict of law principles, and the UN Convention on Contracts for the International Sale of Goods does not apply to this Agreement.
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b. The People's Courts in Hangzhou City shall have exclusive jurisdiction over any dispute arising out of this Agreement.
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README.md
CHANGED
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@@ -1,3 +1,509 @@
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-
---
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license:
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-
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|
| 1 |
+
---
|
| 2 |
+
license: other
|
| 3 |
+
license_name: qwen
|
| 4 |
+
license_link: https://huggingface.co/skt/A.X-4.0/blob/main/LICENSE
|
| 5 |
+
language:
|
| 6 |
+
- en
|
| 7 |
+
- ko
|
| 8 |
+
pipeline_tag: text-generation
|
| 9 |
+
library_name: transformers
|
| 10 |
+
model_id: skt/A.X-4.0
|
| 11 |
+
developers: SKT AI Model Lab
|
| 12 |
+
model-index:
|
| 13 |
+
- name: A.X-4.0
|
| 14 |
+
results:
|
| 15 |
+
- task:
|
| 16 |
+
type: generate_until
|
| 17 |
+
name: mmlu
|
| 18 |
+
dataset:
|
| 19 |
+
name: mmlu (chat CoT)
|
| 20 |
+
type: hails/mmlu_no_train
|
| 21 |
+
metrics:
|
| 22 |
+
- type: exact_match
|
| 23 |
+
value: 86.62
|
| 24 |
+
name: exact_match
|
| 25 |
+
- task:
|
| 26 |
+
type: generate_until
|
| 27 |
+
name: kmmlu
|
| 28 |
+
dataset:
|
| 29 |
+
name: kmmlu (chat CoT)
|
| 30 |
+
type: HAERAE-HUB/KMMLU
|
| 31 |
+
metrics:
|
| 32 |
+
- type: exact_match
|
| 33 |
+
value: 78.32
|
| 34 |
+
name: exact_match
|
| 35 |
+
---
|
| 36 |
+
|
| 37 |
+
# A.X 4.0
|
| 38 |
+
|
| 39 |
+
<p align="center">
|
| 40 |
+
<picture>
|
| 41 |
+
<img src="./assets/A.X_logo_ko_4x3.png" width="45%" style="margin: 40px auto;">
|
| 42 |
+
</picture>
|
| 43 |
+
</p>
|
| 44 |
+
<p align="center"> <a href="https://huggingface.co/collections/skt/ax-4-68637ebaa63b9cc51925e886">🤗 Models</a> | <a href="https://sktax.chat/chat">💬 Chat</a> | <a href="https://github.com/SKT-AI/A.X-4.0">🖥️ Github</a> </p>
|
| 45 |
+
|
| 46 |
+
## A.X 4.0 Family Highlights
|
| 47 |
+
|
| 48 |
+
SK Telecom released **A.X 4.0** (pronounced "A dot X"), a large language model (LLM) optimized for Korean-language understanding and enterprise deployment, on July 03, 2025. Built on the open-source [Qwen2.5](https://huggingface.co/collections/Qwen/qwen25-66e81a666513e518adb90d9e) model, A.X 4.0 has been further trained with large-scale Korean datasets to deliver outstanding performance in real-world business environments.
|
| 49 |
+
|
| 50 |
+
- **Superior Korean Proficiency**: Achieved a score of 78.3 on [KMMLU](https://huggingface.co/datasets/HAERAE-HUB/KMMLU), the leading benchmark for Korean-language evaluation and a Korean-specific adaptation of MMLU, outperforming GPT-4o (72.5).
|
| 51 |
+
- **Deep Cultural Understanding**: Scored 83.5 on [CLIcK](https://huggingface.co/datasets/EunsuKim/CLIcK), a benchmark for Korean cultural and contextual comprehension, surpassing GPT-4o (80.2).
|
| 52 |
+
- **Efficient Token Usage**: A.X 4.0 uses approximately 33% fewer tokens than GPT-4o for the same Korean input, enabling more cost-effective and efficient processing.
|
| 53 |
+
- **Deployment Flexibility**: Offered in both a 72B-parameter standard model (A.X 4.0) and a 7B lightweight version (A.X 4.0 Light).
|
| 54 |
+
- **Long Context Handling**: Supports up to 131,072 tokens, allowing comprehension of lengthy documents and conversations. (Lightweight model supports up to 16,384 tokens length)
|
| 55 |
+
|
| 56 |
+
## Performance
|
| 57 |
+
|
| 58 |
+
### Model Performance
|
| 59 |
+
|
| 60 |
+
<table><thead>
|
| 61 |
+
<tr>
|
| 62 |
+
<th colspan="2">Benchmarks</th>
|
| 63 |
+
<th>A.X 4.0</th>
|
| 64 |
+
<th>Qwen3-235B-A22B<br/>(w/o reasoning)</th>
|
| 65 |
+
<th>Qwen2.5-72B</th>
|
| 66 |
+
<th>GPT-4o</th>
|
| 67 |
+
</tr></thead>
|
| 68 |
+
<tbody>
|
| 69 |
+
<tr>
|
| 70 |
+
<td rowspan="4">Knowledge</td>
|
| 71 |
+
<td>KMMLU</td>
|
| 72 |
+
<td>78.32</td>
|
| 73 |
+
<td>73.64</td>
|
| 74 |
+
<td>66.44</td>
|
| 75 |
+
<td>72.51</td>
|
| 76 |
+
</tr>
|
| 77 |
+
<tr>
|
| 78 |
+
<td>CLIcK</td>
|
| 79 |
+
<td>83.51</td>
|
| 80 |
+
<td>74.55</td>
|
| 81 |
+
<td>72.59</td>
|
| 82 |
+
<td>80.22</td>
|
| 83 |
+
</tr>
|
| 84 |
+
<tr>
|
| 85 |
+
<td>KoBALT</td>
|
| 86 |
+
<td>47.30</td>
|
| 87 |
+
<td>41.57</td>
|
| 88 |
+
<td>37.00</td>
|
| 89 |
+
<td>44.00</td>
|
| 90 |
+
</tr>
|
| 91 |
+
<tr>
|
| 92 |
+
<td>MMLU</td>
|
| 93 |
+
<td>86.62</td>
|
| 94 |
+
<td>87.37</td>
|
| 95 |
+
<td>85.70</td>
|
| 96 |
+
<td>88.70</td>
|
| 97 |
+
</tr>
|
| 98 |
+
<tr>
|
| 99 |
+
<td rowspan="3">General</td>
|
| 100 |
+
<td>Ko-MT-Bench</td>
|
| 101 |
+
<td>86.69</td>
|
| 102 |
+
<td>88.00</td>
|
| 103 |
+
<td>82.69</td>
|
| 104 |
+
<td>88.44</td>
|
| 105 |
+
</tr>
|
| 106 |
+
<tr>
|
| 107 |
+
<td>MT-Bench</td>
|
| 108 |
+
<td>83.25</td>
|
| 109 |
+
<td>86.56</td>
|
| 110 |
+
<td>93.50</td>
|
| 111 |
+
<td>88.19</td>
|
| 112 |
+
</tr>
|
| 113 |
+
<tr>
|
| 114 |
+
<td>LiveBench<sup>2024.11</sup></td>
|
| 115 |
+
<td>52.30</td>
|
| 116 |
+
<td>64.50</td>
|
| 117 |
+
<td>54.20</td>
|
| 118 |
+
<td>52.19</td>
|
| 119 |
+
</tr>
|
| 120 |
+
<tr>
|
| 121 |
+
<td rowspan="2">Instruction Following</td>
|
| 122 |
+
<td>Ko-IFEval</td>
|
| 123 |
+
<td>77.96</td>
|
| 124 |
+
<td>77.53</td>
|
| 125 |
+
<td>77.07</td>
|
| 126 |
+
<td>75.38</td>
|
| 127 |
+
</tr>
|
| 128 |
+
<tr>
|
| 129 |
+
<td>IFEval</td>
|
| 130 |
+
<td>86.05</td>
|
| 131 |
+
<td>85.77</td>
|
| 132 |
+
<td>86.54</td>
|
| 133 |
+
<td>83.86</td>
|
| 134 |
+
</tr>
|
| 135 |
+
<tr>
|
| 136 |
+
<td rowspan="2">Math</td>
|
| 137 |
+
<td>HRM8K</td>
|
| 138 |
+
<td>48.55</td>
|
| 139 |
+
<td>54.52</td>
|
| 140 |
+
<td>46.37</td>
|
| 141 |
+
<td>43.27</td>
|
| 142 |
+
</tr>
|
| 143 |
+
<tr>
|
| 144 |
+
<td>MATH</td>
|
| 145 |
+
<td>74.28</td>
|
| 146 |
+
<td>72.72</td>
|
| 147 |
+
<td>77.00</td>
|
| 148 |
+
<td>72.38</td>
|
| 149 |
+
</tr>
|
| 150 |
+
<tr>
|
| 151 |
+
<td rowspan="3">Code</td>
|
| 152 |
+
<td>HumanEval+</td>
|
| 153 |
+
<td>79.27</td>
|
| 154 |
+
<td>79.27</td>
|
| 155 |
+
<td>81.71</td>
|
| 156 |
+
<td>86.00</td>
|
| 157 |
+
</tr>
|
| 158 |
+
<tr>
|
| 159 |
+
<td>MBPP+</td>
|
| 160 |
+
<td>73.28</td>
|
| 161 |
+
<td>70.11</td>
|
| 162 |
+
<td>75.66</td>
|
| 163 |
+
<td>75.10</td>
|
| 164 |
+
</tr>
|
| 165 |
+
<tr>
|
| 166 |
+
<td>LiveCodeBench<sup>2024.10~2025.04</sup></td>
|
| 167 |
+
<td>26.07</td>
|
| 168 |
+
<td>33.09</td>
|
| 169 |
+
<td>27.58</td>
|
| 170 |
+
<td>29.30</td>
|
| 171 |
+
</tr>
|
| 172 |
+
<tr>
|
| 173 |
+
<td>Long Context</td>
|
| 174 |
+
<td>LongBench<sup><128K</sup></td>
|
| 175 |
+
<td>56.70</td>
|
| 176 |
+
<td>49.40</td>
|
| 177 |
+
<td>45.60</td>
|
| 178 |
+
<td>47.50</td>
|
| 179 |
+
</tr>
|
| 180 |
+
<tr>
|
| 181 |
+
<td>Tool-use</td>
|
| 182 |
+
<td>FunctionChatBench</td>
|
| 183 |
+
<td>85.96</td>
|
| 184 |
+
<td>82.43</td>
|
| 185 |
+
<td>88.30</td>
|
| 186 |
+
<td>95.70</td>
|
| 187 |
+
</tr>
|
| 188 |
+
</tbody></table>
|
| 189 |
+
|
| 190 |
+
### Lightweight Model Performance
|
| 191 |
+
|
| 192 |
+
<table><thead>
|
| 193 |
+
<tr>
|
| 194 |
+
<th colspan="2">Benchmarks</th>
|
| 195 |
+
<th>A.X 4.0 Light</th>
|
| 196 |
+
<th>Qwen3-8B<br/>(w/o reasoning)</th>
|
| 197 |
+
<th>Qwen2.5-7B</th>
|
| 198 |
+
<th>EXAONE-3.5-7.8B</th>
|
| 199 |
+
<th>Kanana-1.5-8B</th>
|
| 200 |
+
</tr></thead>
|
| 201 |
+
<tbody>
|
| 202 |
+
<tr>
|
| 203 |
+
<td rowspan="4">Knowledge</td>
|
| 204 |
+
<td>KMMLU</td>
|
| 205 |
+
<td>64.15</td>
|
| 206 |
+
<td>63.53</td>
|
| 207 |
+
<td>49.56</td>
|
| 208 |
+
<td>53.76</td>
|
| 209 |
+
<td>48.28</td>
|
| 210 |
+
</tr>
|
| 211 |
+
<tr>
|
| 212 |
+
<td>CLIcK</td>
|
| 213 |
+
<td>68.05</td>
|
| 214 |
+
<td>62.71</td>
|
| 215 |
+
<td>60.56</td>
|
| 216 |
+
<td>64.30</td>
|
| 217 |
+
<td>61.30</td>
|
| 218 |
+
</tr>
|
| 219 |
+
<tr>
|
| 220 |
+
<td>KoBALT</td>
|
| 221 |
+
<td>30.29</td>
|
| 222 |
+
<td>26.57</td>
|
| 223 |
+
<td>21.57</td>
|
| 224 |
+
<td>21.71</td>
|
| 225 |
+
<td>23.14</td>
|
| 226 |
+
</tr>
|
| 227 |
+
<tr>
|
| 228 |
+
<td>MMLU</td>
|
| 229 |
+
<td>75.43</td>
|
| 230 |
+
<td>82.89</td>
|
| 231 |
+
<td>75.40</td>
|
| 232 |
+
<td>72.20</td>
|
| 233 |
+
<td>68.82</td>
|
| 234 |
+
</tr>
|
| 235 |
+
<tr>
|
| 236 |
+
<td rowspan="3">General</td>
|
| 237 |
+
<td>Ko-MT-Bench</td>
|
| 238 |
+
<td>79.50</td>
|
| 239 |
+
<td>64.06</td>
|
| 240 |
+
<td>61.31</td>
|
| 241 |
+
<td>81.06</td>
|
| 242 |
+
<td>76.30</td>
|
| 243 |
+
</tr>
|
| 244 |
+
<tr>
|
| 245 |
+
<td>MT-Bench</td>
|
| 246 |
+
<td>81.56</td>
|
| 247 |
+
<td>65.69</td>
|
| 248 |
+
<td>79.37</td>
|
| 249 |
+
<td>83.50</td>
|
| 250 |
+
<td>77.60</td>
|
| 251 |
+
</tr>
|
| 252 |
+
<tr>
|
| 253 |
+
<td>LiveBench</td>
|
| 254 |
+
<td>37.10</td>
|
| 255 |
+
<td>50.20</td>
|
| 256 |
+
<td>37.00</td>
|
| 257 |
+
<td>40.20</td>
|
| 258 |
+
<td>29.40</td>
|
| 259 |
+
</tr>
|
| 260 |
+
<tr>
|
| 261 |
+
<td rowspan="2">Instruction Following</td>
|
| 262 |
+
<td>Ko-IFEval</td>
|
| 263 |
+
<td>72.99</td>
|
| 264 |
+
<td>73.39</td>
|
| 265 |
+
<td>60.73</td>
|
| 266 |
+
<td>65.01</td>
|
| 267 |
+
<td>69.96</td>
|
| 268 |
+
</tr>
|
| 269 |
+
<tr>
|
| 270 |
+
<td>IFEval</td>
|
| 271 |
+
<td>84.68</td>
|
| 272 |
+
<td>85.38</td>
|
| 273 |
+
<td>76.73</td>
|
| 274 |
+
<td>82.61</td>
|
| 275 |
+
<td>80.11</td>
|
| 276 |
+
</tr>
|
| 277 |
+
<tr>
|
| 278 |
+
<td rowspan="2">Math</td>
|
| 279 |
+
<td>HRM8K</td>
|
| 280 |
+
<td>40.12</td>
|
| 281 |
+
<td>52.50</td>
|
| 282 |
+
<td>35.13</td>
|
| 283 |
+
<td>31.88</td>
|
| 284 |
+
<td>30.87</td>
|
| 285 |
+
</tr>
|
| 286 |
+
<tr>
|
| 287 |
+
<td>MATH</td>
|
| 288 |
+
<td>68.88</td>
|
| 289 |
+
<td>71.48</td>
|
| 290 |
+
<td>65.58</td>
|
| 291 |
+
<td>63.20</td>
|
| 292 |
+
<td>59.28</td>
|
| 293 |
+
</tr>
|
| 294 |
+
<tr>
|
| 295 |
+
<td rowspan="3">Code</td>
|
| 296 |
+
<td>HumanEval+</td>
|
| 297 |
+
<td>75.61</td>
|
| 298 |
+
<td>77.44</td>
|
| 299 |
+
<td>74.39</td>
|
| 300 |
+
<td>76.83</td>
|
| 301 |
+
<td>76.83</td>
|
| 302 |
+
</tr>
|
| 303 |
+
<tr>
|
| 304 |
+
<td>MBPP+</td>
|
| 305 |
+
<td>67.20</td>
|
| 306 |
+
<td>62.17</td>
|
| 307 |
+
<td>68.50</td>
|
| 308 |
+
<td>64.29</td>
|
| 309 |
+
<td>67.99</td>
|
| 310 |
+
</tr>
|
| 311 |
+
<tr>
|
| 312 |
+
<td>LiveCodeBench</td>
|
| 313 |
+
<td>18.03</td>
|
| 314 |
+
<td>23.93</td>
|
| 315 |
+
<td>16.62</td>
|
| 316 |
+
<td>17.98</td>
|
| 317 |
+
<td>16.52</td>
|
| 318 |
+
</tr>
|
| 319 |
+
</tbody></table>
|
| 320 |
+
|
| 321 |
+
## 🚀 Quickstart
|
| 322 |
+
|
| 323 |
+
### with HuggingFace Transformers
|
| 324 |
+
|
| 325 |
+
- `transformers>=4.46.0` or the latest version is required to use `skt/A.X-4.0`
|
| 326 |
+
```bash
|
| 327 |
+
pip install transformers>=4.46.0
|
| 328 |
+
```
|
| 329 |
+
|
| 330 |
+
#### Example Usage
|
| 331 |
+
|
| 332 |
+
```python
|
| 333 |
+
import torch
|
| 334 |
+
from transformers import AutoModelForCausalLM, AutoTokenizer
|
| 335 |
+
|
| 336 |
+
model_name = "skt/A.X-4.0"
|
| 337 |
+
model = AutoModelForCausalLM.from_pretrained(
|
| 338 |
+
model_name,
|
| 339 |
+
torch_dtype=torch.bfloat16,
|
| 340 |
+
device_map="auto",
|
| 341 |
+
)
|
| 342 |
+
model.eval()
|
| 343 |
+
tokenizer = AutoTokenizer.from_pretrained(model_name)
|
| 344 |
+
|
| 345 |
+
messages = [
|
| 346 |
+
{"role": "system", "content": "당신은 사용자가 제공하는 영어 문장들을 한국어로 번역하는 AI 전문가입니다."},
|
| 347 |
+
{"role": "user", "content": "The first human went into space and orbited the Earth on April 12, 1961."},
|
| 348 |
+
]
|
| 349 |
+
input_ids = tokenizer.apply_chat_template(messages, add_generation_prompt=True, return_tensors="pt").to(model.device)
|
| 350 |
+
|
| 351 |
+
with torch.no_grad():
|
| 352 |
+
output = model.generate(
|
| 353 |
+
input_ids,
|
| 354 |
+
max_new_tokens=128,
|
| 355 |
+
do_sample=False,
|
| 356 |
+
)
|
| 357 |
+
|
| 358 |
+
len_input_prompt = len(input_ids[0])
|
| 359 |
+
response = tokenizer.decode(output[0][len_input_prompt:], skip_special_tokens=True)
|
| 360 |
+
print(response)
|
| 361 |
+
# Output:
|
| 362 |
+
# 최초의 인간이 1961년 4월 12일에 우주로 가서 지구 궤도를 돌았습니다.
|
| 363 |
+
```
|
| 364 |
+
|
| 365 |
+
### with vLLM
|
| 366 |
+
|
| 367 |
+
- `vllm>=v0.6.4.post1` or the latest version is required to use tool-use function
|
| 368 |
+
```bash
|
| 369 |
+
pip install vllm>=v0.6.4.post1
|
| 370 |
+
# if you don't want to activate tool-use function, just commenting out below vLLM option
|
| 371 |
+
VLLM_OPTION="--enable-auto-tool-choice --tool-call-parser hermes"
|
| 372 |
+
vllm serve skt/A.X-4.0 $VLLM_OPTION
|
| 373 |
+
```
|
| 374 |
+
|
| 375 |
+
#### Example Usage
|
| 376 |
+
|
| 377 |
+
```python
|
| 378 |
+
from openai import OpenAI
|
| 379 |
+
|
| 380 |
+
def call(messages, model):
|
| 381 |
+
completion = client.chat.completions.create(
|
| 382 |
+
model=model,
|
| 383 |
+
messages=messages,
|
| 384 |
+
)
|
| 385 |
+
print(completion.choices[0].message)
|
| 386 |
+
|
| 387 |
+
client = OpenAI(
|
| 388 |
+
base_url="http://localhost:8000/v1",
|
| 389 |
+
api_key="api_key"
|
| 390 |
+
)
|
| 391 |
+
model = "skt/A.X-4.0"
|
| 392 |
+
messages = [{"role": "user", "content": "에어컨 여름철 적정 온도는? 한줄로 답변해줘"}]
|
| 393 |
+
call(messages, model)
|
| 394 |
+
# Output:
|
| 395 |
+
# ChatCompletionMessage(content='여름철 에어컨 적정 온도는 24~26도입니다.', refusal=None, role='assistant', audio=None, function_call=None, tool_calls=[], reasoning_content=None)
|
| 396 |
+
|
| 397 |
+
messages = [{"role": "user", "content": "What is the appropriate temperature for air conditioning in summer? Response in a single sentence."}]
|
| 398 |
+
call(messages, model)
|
| 399 |
+
# Output:
|
| 400 |
+
# ChatCompletionMessage(content='A comfortable and energy-efficient temperature for air conditioning in summer is typically around 24-26°C (75-79°F).', refusal=None, role='assistant', audio=None, function_call=None, tool_calls=[], reasoning_content=None)
|
| 401 |
+
```
|
| 402 |
+
|
| 403 |
+
#### Examples for tool-use
|
| 404 |
+
```python
|
| 405 |
+
from openai import OpenAI
|
| 406 |
+
|
| 407 |
+
|
| 408 |
+
def call(messages, model):
|
| 409 |
+
completion = client.chat.completions.create(
|
| 410 |
+
model=model,
|
| 411 |
+
messages=messages,
|
| 412 |
+
tools=tools
|
| 413 |
+
)
|
| 414 |
+
print(completion.choices[0].message)
|
| 415 |
+
|
| 416 |
+
|
| 417 |
+
client = OpenAI(
|
| 418 |
+
base_url="http://ip:port/v1",
|
| 419 |
+
api_key="api_key"
|
| 420 |
+
)
|
| 421 |
+
model = "skt/A.X-4.0"
|
| 422 |
+
|
| 423 |
+
calculate_discount = {
|
| 424 |
+
"type": "function",
|
| 425 |
+
"function": {
|
| 426 |
+
"name": "calculate_discount",
|
| 427 |
+
"description": "원가격과 할인율(퍼센트 단위)을 입력받아 할인된 가격을계산한다.",
|
| 428 |
+
"parameters": {
|
| 429 |
+
"type": "object",
|
| 430 |
+
"properties": {
|
| 431 |
+
"original_price": {
|
| 432 |
+
"type": "number",
|
| 433 |
+
"description": "상품의 원래 가격"
|
| 434 |
+
},
|
| 435 |
+
"discount_percentage": {
|
| 436 |
+
"type": "number",
|
| 437 |
+
"description": "적용할 할인율(예: 20% 할인의 경우 20을 입력)"
|
| 438 |
+
}
|
| 439 |
+
},
|
| 440 |
+
"required": ["original_price", "discount_percentage"]
|
| 441 |
+
}
|
| 442 |
+
}
|
| 443 |
+
}
|
| 444 |
+
get_exchange_rate = {
|
| 445 |
+
"type": "function",
|
| 446 |
+
"function": {
|
| 447 |
+
"name": "get_exchange_rate",
|
| 448 |
+
"description": "두 통화 간의 환율을 가져온다.",
|
| 449 |
+
"parameters": {
|
| 450 |
+
"type": "object",
|
| 451 |
+
"properties": {
|
| 452 |
+
"base_currency": {
|
| 453 |
+
"type": "string",
|
| 454 |
+
"description": "The currency to convert from."
|
| 455 |
+
},
|
| 456 |
+
"target_currency": {
|
| 457 |
+
"type": "string",
|
| 458 |
+
"description": "The currency to convert to."
|
| 459 |
+
}
|
| 460 |
+
},
|
| 461 |
+
"required": ["base_currency", "target_currency"]
|
| 462 |
+
}
|
| 463 |
+
}
|
| 464 |
+
}
|
| 465 |
+
tools = [calculate_discount, get_exchange_rate]
|
| 466 |
+
|
| 467 |
+
### Slot filling ###
|
| 468 |
+
messages = [{"role": "user", "content": "우리가 뭘 사야되는데 원래 57600원인데 직원할인 받을 수 있거든? 할인가좀 계산해줘"}]
|
| 469 |
+
call(messages, model)
|
| 470 |
+
# Output:
|
| 471 |
+
# ChatCompletionMessage(content='직원 할인을 몇 퍼센트 받을 수 있는지 알려주시겠어요?', refusal=None, role='assistant', audio=None, function_call=None, tool_calls=[], reasoning_content=None)
|
| 472 |
+
|
| 473 |
+
|
| 474 |
+
### Function calling ###
|
| 475 |
+
messages = [
|
| 476 |
+
{"role": "user", "content": "우리가 뭘 사야되는데 원래 57600원인데 직원할인 받을 수 있거든? 할인가좀 계산해줘"},
|
| 477 |
+
{"role": "assistant", "content": "직원 할인을 몇 퍼센트 받을 수 있는지 알려주시겠어요?"},
|
| 478 |
+
{"role": "user", "content": "15% 할인 받을 수 있어."},
|
| 479 |
+
]
|
| 480 |
+
call(messages, model)
|
| 481 |
+
# Output:
|
| 482 |
+
# ChatCompletionMessage(content=None, refusal=None, role='assistant', audio=None, function_call=None, tool_calls=[ChatCompletionMessageToolCall(id='chatcmpl-tool-8634f423e5494ebfa7a428b8385b4981', function=Function(arguments='{"original_price": 57600, "discount_percentage": 15}', name='calculate_discount'), type='function')], reasoning_content=None)
|
| 483 |
+
|
| 484 |
+
|
| 485 |
+
### Completion ###
|
| 486 |
+
messages = [
|
| 487 |
+
{"role": "user", "content": "우리가 뭘 사야되는데 원래 57600원인데 직원할인 받을 수 있거든? 할인가좀 계산해줘"},
|
| 488 |
+
{"role": "assistant", "content": "직원 할인을 몇 퍼센트 받을 수 있는지 알려주시겠어요?"},
|
| 489 |
+
{"role": "user", "content": "15% 할인 받을 수 있어."},
|
| 490 |
+
{"role": "tool", "tool_call_id": "random_id", "name": "calculate_discount", "content": "{\"original_price\": 57600, \"discount_percentage\": 15, \"discounted_price\": 48960.0}"}
|
| 491 |
+
]
|
| 492 |
+
call(messages, model)
|
| 493 |
+
# Output:
|
| 494 |
+
# ChatCompletionMessage(content='15% 할인을 적용하면 상품의 가격은 48,960원이 됩니다.', refusal=None, role='assistant', audio=None, function_call=None, tool_calls=[], reasoning_content=None)
|
| 495 |
+
```
|
| 496 |
+
|
| 497 |
+
## Citation
|
| 498 |
+
```
|
| 499 |
+
@article{SKTAdotX4,
|
| 500 |
+
title={A.X 4.0},
|
| 501 |
+
author={SKT AI Model Lab},
|
| 502 |
+
year={2025},
|
| 503 |
+
url={https://huggingface.co/skt/A.X-4.0}
|
| 504 |
+
}
|
| 505 |
+
```
|
| 506 |
+
|
| 507 |
+
## Contact
|
| 508 |
+
|
| 509 |
+
- Business & Partnership Contact: [[email protected]]([email protected])
|
assets/A.X_logo.png
ADDED
|
assets/A.X_logo_ko_4x3.png
ADDED
|
Git LFS Details
|
generation_config.json
ADDED
|
@@ -0,0 +1,9 @@
|
|
|
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|
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|
| 1 |
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{
|
| 2 |
+
"bos_token_id": 0,
|
| 3 |
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"do_sample": true,
|
| 4 |
+
"eos_token_id": 27,
|
| 5 |
+
"pad_token_id": 1,
|
| 6 |
+
"temperature": 0.6,
|
| 7 |
+
"top_p": 0.95,
|
| 8 |
+
"transformers_version": "4.46.0"
|
| 9 |
+
}
|
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ADDED
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model-00025-of-00030.safetensors
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model-00026-of-00030.safetensors
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version https://git-lfs.github.com/spec/v1
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model-00027-of-00030.safetensors
ADDED
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| 1 |
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version https://git-lfs.github.com/spec/v1
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model-00028-of-00030.safetensors
ADDED
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| 1 |
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version https://git-lfs.github.com/spec/v1
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| 3 |
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size 4964101416
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model-00029-of-00030.safetensors
ADDED
|
@@ -0,0 +1,3 @@
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| 1 |
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version https://git-lfs.github.com/spec/v1
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size 4781637360
|
model-00030-of-00030.safetensors
ADDED
|
@@ -0,0 +1,3 @@
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| 1 |
+
version https://git-lfs.github.com/spec/v1
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size 3917584288
|
model.safetensors.index.json
ADDED
|
@@ -0,0 +1,970 @@
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pytorch_model.bin.index.json
ADDED
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| 1 |
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| 2 |
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
| 956 |
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|
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|
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|
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|
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|
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|
| 962 |
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|
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|
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|
| 965 |
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|
| 966 |
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|
| 967 |
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|
| 968 |
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|
| 969 |
+
}
|
| 970 |
+
}
|
special_tokens_map.json
ADDED
|
@@ -0,0 +1,90 @@
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|
| 1 |
+
{
|
| 2 |
+
"additional_special_tokens": [
|
| 3 |
+
"<|endoftext|>",
|
| 4 |
+
"<|pad|>",
|
| 5 |
+
"<|unk|>",
|
| 6 |
+
"<|sep|>",
|
| 7 |
+
"<|mask|>",
|
| 8 |
+
"<|cls|>",
|
| 9 |
+
"<|image|>",
|
| 10 |
+
"<|audio|>",
|
| 11 |
+
"<|user|>",
|
| 12 |
+
"<|system|>",
|
| 13 |
+
"<|assistant|>",
|
| 14 |
+
"<|extra_id_0|>",
|
| 15 |
+
"<|extra_id_1|>",
|
| 16 |
+
"<|extra_id_2|>",
|
| 17 |
+
"<|extra_id_3|>",
|
| 18 |
+
"<|extra_id_4|>",
|
| 19 |
+
"<|extra_id_5|>",
|
| 20 |
+
"<|extra_id_6|>",
|
| 21 |
+
"<|extra_id_7|>",
|
| 22 |
+
"<|extra_id_8|>",
|
| 23 |
+
"<|extra_id_9|>",
|
| 24 |
+
"<|extra_id_10|>",
|
| 25 |
+
"<|extra_id_11|>",
|
| 26 |
+
"<|extra_id_12|>",
|
| 27 |
+
"<|extra_id_13|>",
|
| 28 |
+
"<|im_start|>",
|
| 29 |
+
"<|im_sep|>",
|
| 30 |
+
"<|im_end|>",
|
| 31 |
+
"<|resident_reg|>",
|
| 32 |
+
"<|foreigner_reg|>",
|
| 33 |
+
"<|business_reg|>",
|
| 34 |
+
"<|credit_card|>",
|
| 35 |
+
"<|passport|>",
|
| 36 |
+
"<|driver_license|>",
|
| 37 |
+
"<|telephone|>",
|
| 38 |
+
"<|health_insurance|>",
|
| 39 |
+
"<|bank_account|>"
|
| 40 |
+
],
|
| 41 |
+
"bos_token": {
|
| 42 |
+
"content": "<|endoftext|>",
|
| 43 |
+
"lstrip": false,
|
| 44 |
+
"normalized": false,
|
| 45 |
+
"rstrip": false,
|
| 46 |
+
"single_word": false
|
| 47 |
+
},
|
| 48 |
+
"cls_token": {
|
| 49 |
+
"content": "<|cls|>",
|
| 50 |
+
"lstrip": false,
|
| 51 |
+
"normalized": false,
|
| 52 |
+
"rstrip": false,
|
| 53 |
+
"single_word": false
|
| 54 |
+
},
|
| 55 |
+
"eos_token": {
|
| 56 |
+
"content": "<|im_end|>",
|
| 57 |
+
"lstrip": false,
|
| 58 |
+
"normalized": false,
|
| 59 |
+
"rstrip": false,
|
| 60 |
+
"single_word": false
|
| 61 |
+
},
|
| 62 |
+
"mask_token": {
|
| 63 |
+
"content": "<|mask|>",
|
| 64 |
+
"lstrip": false,
|
| 65 |
+
"normalized": false,
|
| 66 |
+
"rstrip": false,
|
| 67 |
+
"single_word": false
|
| 68 |
+
},
|
| 69 |
+
"pad_token": {
|
| 70 |
+
"content": "<|pad|>",
|
| 71 |
+
"lstrip": false,
|
| 72 |
+
"normalized": false,
|
| 73 |
+
"rstrip": false,
|
| 74 |
+
"single_word": false
|
| 75 |
+
},
|
| 76 |
+
"sep_token": {
|
| 77 |
+
"content": "<|sep|>",
|
| 78 |
+
"lstrip": false,
|
| 79 |
+
"normalized": false,
|
| 80 |
+
"rstrip": false,
|
| 81 |
+
"single_word": false
|
| 82 |
+
},
|
| 83 |
+
"unk_token": {
|
| 84 |
+
"content": "<|unk|>",
|
| 85 |
+
"lstrip": false,
|
| 86 |
+
"normalized": false,
|
| 87 |
+
"rstrip": false,
|
| 88 |
+
"single_word": false
|
| 89 |
+
}
|
| 90 |
+
}
|
tokenizer_config.json
ADDED
|
@@ -0,0 +1,391 @@
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|
|
| 1 |
+
{
|
| 2 |
+
"add_bos_token": false,
|
| 3 |
+
"add_prefix_space": false,
|
| 4 |
+
"added_tokens_decoder": {
|
| 5 |
+
"0": {
|
| 6 |
+
"content": "<|endoftext|>",
|
| 7 |
+
"lstrip": false,
|
| 8 |
+
"normalized": false,
|
| 9 |
+
"rstrip": false,
|
| 10 |
+
"single_word": false,
|
| 11 |
+
"special": true
|
| 12 |
+
},
|
| 13 |
+
"1": {
|
| 14 |
+
"content": "<|pad|>",
|
| 15 |
+
"lstrip": false,
|
| 16 |
+
"normalized": false,
|
| 17 |
+
"rstrip": false,
|
| 18 |
+
"single_word": false,
|
| 19 |
+
"special": true
|
| 20 |
+
},
|
| 21 |
+
"2": {
|
| 22 |
+
"content": "<|unk|>",
|
| 23 |
+
"lstrip": false,
|
| 24 |
+
"normalized": false,
|
| 25 |
+
"rstrip": false,
|
| 26 |
+
"single_word": false,
|
| 27 |
+
"special": true
|
| 28 |
+
},
|
| 29 |
+
"3": {
|
| 30 |
+
"content": "<|sep|>",
|
| 31 |
+
"lstrip": false,
|
| 32 |
+
"normalized": false,
|
| 33 |
+
"rstrip": false,
|
| 34 |
+
"single_word": false,
|
| 35 |
+
"special": true
|
| 36 |
+
},
|
| 37 |
+
"4": {
|
| 38 |
+
"content": "<|mask|>",
|
| 39 |
+
"lstrip": false,
|
| 40 |
+
"normalized": false,
|
| 41 |
+
"rstrip": false,
|
| 42 |
+
"single_word": false,
|
| 43 |
+
"special": true
|
| 44 |
+
},
|
| 45 |
+
"5": {
|
| 46 |
+
"content": "<|cls|>",
|
| 47 |
+
"lstrip": false,
|
| 48 |
+
"normalized": false,
|
| 49 |
+
"rstrip": false,
|
| 50 |
+
"single_word": false,
|
| 51 |
+
"special": true
|
| 52 |
+
},
|
| 53 |
+
"6": {
|
| 54 |
+
"content": "<|image|>",
|
| 55 |
+
"lstrip": false,
|
| 56 |
+
"normalized": false,
|
| 57 |
+
"rstrip": false,
|
| 58 |
+
"single_word": false,
|
| 59 |
+
"special": true
|
| 60 |
+
},
|
| 61 |
+
"7": {
|
| 62 |
+
"content": "<|audio|>",
|
| 63 |
+
"lstrip": false,
|
| 64 |
+
"normalized": false,
|
| 65 |
+
"rstrip": false,
|
| 66 |
+
"single_word": false,
|
| 67 |
+
"special": true
|
| 68 |
+
},
|
| 69 |
+
"8": {
|
| 70 |
+
"content": "<|user|>",
|
| 71 |
+
"lstrip": false,
|
| 72 |
+
"normalized": false,
|
| 73 |
+
"rstrip": false,
|
| 74 |
+
"single_word": false,
|
| 75 |
+
"special": true
|
| 76 |
+
},
|
| 77 |
+
"9": {
|
| 78 |
+
"content": "<|system|>",
|
| 79 |
+
"lstrip": false,
|
| 80 |
+
"normalized": false,
|
| 81 |
+
"rstrip": false,
|
| 82 |
+
"single_word": false,
|
| 83 |
+
"special": true
|
| 84 |
+
},
|
| 85 |
+
"10": {
|
| 86 |
+
"content": "<|assistant|>",
|
| 87 |
+
"lstrip": false,
|
| 88 |
+
"normalized": false,
|
| 89 |
+
"rstrip": false,
|
| 90 |
+
"single_word": false,
|
| 91 |
+
"special": true
|
| 92 |
+
},
|
| 93 |
+
"11": {
|
| 94 |
+
"content": "<|extra_id_0|>",
|
| 95 |
+
"lstrip": false,
|
| 96 |
+
"normalized": false,
|
| 97 |
+
"rstrip": false,
|
| 98 |
+
"single_word": false,
|
| 99 |
+
"special": true
|
| 100 |
+
},
|
| 101 |
+
"12": {
|
| 102 |
+
"content": "<|extra_id_1|>",
|
| 103 |
+
"lstrip": false,
|
| 104 |
+
"normalized": false,
|
| 105 |
+
"rstrip": false,
|
| 106 |
+
"single_word": false,
|
| 107 |
+
"special": true
|
| 108 |
+
},
|
| 109 |
+
"13": {
|
| 110 |
+
"content": "<|extra_id_2|>",
|
| 111 |
+
"lstrip": false,
|
| 112 |
+
"normalized": false,
|
| 113 |
+
"rstrip": false,
|
| 114 |
+
"single_word": false,
|
| 115 |
+
"special": true
|
| 116 |
+
},
|
| 117 |
+
"14": {
|
| 118 |
+
"content": "<|extra_id_3|>",
|
| 119 |
+
"lstrip": false,
|
| 120 |
+
"normalized": false,
|
| 121 |
+
"rstrip": false,
|
| 122 |
+
"single_word": false,
|
| 123 |
+
"special": true
|
| 124 |
+
},
|
| 125 |
+
"15": {
|
| 126 |
+
"content": "<|extra_id_4|>",
|
| 127 |
+
"lstrip": false,
|
| 128 |
+
"normalized": false,
|
| 129 |
+
"rstrip": false,
|
| 130 |
+
"single_word": false,
|
| 131 |
+
"special": true
|
| 132 |
+
},
|
| 133 |
+
"16": {
|
| 134 |
+
"content": "<|extra_id_5|>",
|
| 135 |
+
"lstrip": false,
|
| 136 |
+
"normalized": false,
|
| 137 |
+
"rstrip": false,
|
| 138 |
+
"single_word": false,
|
| 139 |
+
"special": true
|
| 140 |
+
},
|
| 141 |
+
"17": {
|
| 142 |
+
"content": "<|extra_id_6|>",
|
| 143 |
+
"lstrip": false,
|
| 144 |
+
"normalized": false,
|
| 145 |
+
"rstrip": false,
|
| 146 |
+
"single_word": false,
|
| 147 |
+
"special": true
|
| 148 |
+
},
|
| 149 |
+
"18": {
|
| 150 |
+
"content": "<|extra_id_7|>",
|
| 151 |
+
"lstrip": false,
|
| 152 |
+
"normalized": false,
|
| 153 |
+
"rstrip": false,
|
| 154 |
+
"single_word": false,
|
| 155 |
+
"special": true
|
| 156 |
+
},
|
| 157 |
+
"19": {
|
| 158 |
+
"content": "<|extra_id_8|>",
|
| 159 |
+
"lstrip": false,
|
| 160 |
+
"normalized": false,
|
| 161 |
+
"rstrip": false,
|
| 162 |
+
"single_word": false,
|
| 163 |
+
"special": true
|
| 164 |
+
},
|
| 165 |
+
"20": {
|
| 166 |
+
"content": "<|extra_id_9|>",
|
| 167 |
+
"lstrip": false,
|
| 168 |
+
"normalized": false,
|
| 169 |
+
"rstrip": false,
|
| 170 |
+
"single_word": false,
|
| 171 |
+
"special": true
|
| 172 |
+
},
|
| 173 |
+
"21": {
|
| 174 |
+
"content": "<|extra_id_10|>",
|
| 175 |
+
"lstrip": false,
|
| 176 |
+
"normalized": false,
|
| 177 |
+
"rstrip": false,
|
| 178 |
+
"single_word": false,
|
| 179 |
+
"special": true
|
| 180 |
+
},
|
| 181 |
+
"22": {
|
| 182 |
+
"content": "<|extra_id_11|>",
|
| 183 |
+
"lstrip": false,
|
| 184 |
+
"normalized": false,
|
| 185 |
+
"rstrip": false,
|
| 186 |
+
"single_word": false,
|
| 187 |
+
"special": true
|
| 188 |
+
},
|
| 189 |
+
"23": {
|
| 190 |
+
"content": "<|extra_id_12|>",
|
| 191 |
+
"lstrip": false,
|
| 192 |
+
"normalized": false,
|
| 193 |
+
"rstrip": false,
|
| 194 |
+
"single_word": false,
|
| 195 |
+
"special": true
|
| 196 |
+
},
|
| 197 |
+
"24": {
|
| 198 |
+
"content": "<|extra_id_13|>",
|
| 199 |
+
"lstrip": false,
|
| 200 |
+
"normalized": false,
|
| 201 |
+
"rstrip": false,
|
| 202 |
+
"single_word": false,
|
| 203 |
+
"special": true
|
| 204 |
+
},
|
| 205 |
+
"25": {
|
| 206 |
+
"content": "<|im_start|>",
|
| 207 |
+
"lstrip": false,
|
| 208 |
+
"normalized": false,
|
| 209 |
+
"rstrip": false,
|
| 210 |
+
"single_word": false,
|
| 211 |
+
"special": true
|
| 212 |
+
},
|
| 213 |
+
"26": {
|
| 214 |
+
"content": "<|im_sep|>",
|
| 215 |
+
"lstrip": false,
|
| 216 |
+
"normalized": false,
|
| 217 |
+
"rstrip": false,
|
| 218 |
+
"single_word": false,
|
| 219 |
+
"special": true
|
| 220 |
+
},
|
| 221 |
+
"27": {
|
| 222 |
+
"content": "<|im_end|>",
|
| 223 |
+
"lstrip": false,
|
| 224 |
+
"normalized": false,
|
| 225 |
+
"rstrip": false,
|
| 226 |
+
"single_word": false,
|
| 227 |
+
"special": true
|
| 228 |
+
},
|
| 229 |
+
"28": {
|
| 230 |
+
"content": "<|resident_reg|>",
|
| 231 |
+
"lstrip": false,
|
| 232 |
+
"normalized": false,
|
| 233 |
+
"rstrip": false,
|
| 234 |
+
"single_word": false,
|
| 235 |
+
"special": true
|
| 236 |
+
},
|
| 237 |
+
"29": {
|
| 238 |
+
"content": "<|foreigner_reg|>",
|
| 239 |
+
"lstrip": false,
|
| 240 |
+
"normalized": false,
|
| 241 |
+
"rstrip": false,
|
| 242 |
+
"single_word": false,
|
| 243 |
+
"special": true
|
| 244 |
+
},
|
| 245 |
+
"30": {
|
| 246 |
+
"content": "<|business_reg|>",
|
| 247 |
+
"lstrip": false,
|
| 248 |
+
"normalized": false,
|
| 249 |
+
"rstrip": false,
|
| 250 |
+
"single_word": false,
|
| 251 |
+
"special": true
|
| 252 |
+
},
|
| 253 |
+
"31": {
|
| 254 |
+
"content": "<|credit_card|>",
|
| 255 |
+
"lstrip": false,
|
| 256 |
+
"normalized": false,
|
| 257 |
+
"rstrip": false,
|
| 258 |
+
"single_word": false,
|
| 259 |
+
"special": true
|
| 260 |
+
},
|
| 261 |
+
"32": {
|
| 262 |
+
"content": "<|passport|>",
|
| 263 |
+
"lstrip": false,
|
| 264 |
+
"normalized": false,
|
| 265 |
+
"rstrip": false,
|
| 266 |
+
"single_word": false,
|
| 267 |
+
"special": true
|
| 268 |
+
},
|
| 269 |
+
"33": {
|
| 270 |
+
"content": "<|driver_license|>",
|
| 271 |
+
"lstrip": false,
|
| 272 |
+
"normalized": false,
|
| 273 |
+
"rstrip": false,
|
| 274 |
+
"single_word": false,
|
| 275 |
+
"special": true
|
| 276 |
+
},
|
| 277 |
+
"34": {
|
| 278 |
+
"content": "<|telephone|>",
|
| 279 |
+
"lstrip": false,
|
| 280 |
+
"normalized": false,
|
| 281 |
+
"rstrip": false,
|
| 282 |
+
"single_word": false,
|
| 283 |
+
"special": true
|
| 284 |
+
},
|
| 285 |
+
"35": {
|
| 286 |
+
"content": "<|health_insurance|>",
|
| 287 |
+
"lstrip": false,
|
| 288 |
+
"normalized": false,
|
| 289 |
+
"rstrip": false,
|
| 290 |
+
"single_word": false,
|
| 291 |
+
"special": true
|
| 292 |
+
},
|
| 293 |
+
"36": {
|
| 294 |
+
"content": "<|bank_account|>",
|
| 295 |
+
"lstrip": false,
|
| 296 |
+
"normalized": false,
|
| 297 |
+
"rstrip": false,
|
| 298 |
+
"single_word": false,
|
| 299 |
+
"special": true
|
| 300 |
+
},
|
| 301 |
+
"37": {
|
| 302 |
+
"content": "</tool_output>",
|
| 303 |
+
"lstrip": false,
|
| 304 |
+
"normalized": false,
|
| 305 |
+
"rstrip": false,
|
| 306 |
+
"single_word": false,
|
| 307 |
+
"special": false
|
| 308 |
+
},
|
| 309 |
+
"38": {
|
| 310 |
+
"content": "<tool_output>",
|
| 311 |
+
"lstrip": false,
|
| 312 |
+
"normalized": false,
|
| 313 |
+
"rstrip": false,
|
| 314 |
+
"single_word": false,
|
| 315 |
+
"special": false
|
| 316 |
+
},
|
| 317 |
+
"39": {
|
| 318 |
+
"content": "</tool_call>",
|
| 319 |
+
"lstrip": false,
|
| 320 |
+
"normalized": false,
|
| 321 |
+
"rstrip": false,
|
| 322 |
+
"single_word": false,
|
| 323 |
+
"special": false
|
| 324 |
+
},
|
| 325 |
+
"40": {
|
| 326 |
+
"content": "<tool_call>",
|
| 327 |
+
"lstrip": false,
|
| 328 |
+
"normalized": false,
|
| 329 |
+
"rstrip": false,
|
| 330 |
+
"single_word": false,
|
| 331 |
+
"special": false
|
| 332 |
+
}
|
| 333 |
+
},
|
| 334 |
+
"additional_special_tokens": [
|
| 335 |
+
"<|endoftext|>",
|
| 336 |
+
"<|pad|>",
|
| 337 |
+
"<|unk|>",
|
| 338 |
+
"<|sep|>",
|
| 339 |
+
"<|mask|>",
|
| 340 |
+
"<|cls|>",
|
| 341 |
+
"<|image|>",
|
| 342 |
+
"<|audio|>",
|
| 343 |
+
"<|user|>",
|
| 344 |
+
"<|system|>",
|
| 345 |
+
"<|assistant|>",
|
| 346 |
+
"<|extra_id_0|>",
|
| 347 |
+
"<|extra_id_1|>",
|
| 348 |
+
"<|extra_id_2|>",
|
| 349 |
+
"<|extra_id_3|>",
|
| 350 |
+
"<|extra_id_4|>",
|
| 351 |
+
"<|extra_id_5|>",
|
| 352 |
+
"<|extra_id_6|>",
|
| 353 |
+
"<|extra_id_7|>",
|
| 354 |
+
"<|extra_id_8|>",
|
| 355 |
+
"<|extra_id_9|>",
|
| 356 |
+
"<|extra_id_10|>",
|
| 357 |
+
"<|extra_id_11|>",
|
| 358 |
+
"<|extra_id_12|>",
|
| 359 |
+
"<|extra_id_13|>",
|
| 360 |
+
"<|im_start|>",
|
| 361 |
+
"<|im_sep|>",
|
| 362 |
+
"<|im_end|>",
|
| 363 |
+
"<|resident_reg|>",
|
| 364 |
+
"<|foreigner_reg|>",
|
| 365 |
+
"<|business_reg|>",
|
| 366 |
+
"<|credit_card|>",
|
| 367 |
+
"<|passport|>",
|
| 368 |
+
"<|driver_license|>",
|
| 369 |
+
"<|telephone|>",
|
| 370 |
+
"<|health_insurance|>",
|
| 371 |
+
"<|bank_account|>"
|
| 372 |
+
],
|
| 373 |
+
"bos_token": "<|endoftext|>",
|
| 374 |
+
"chat_template": "{%- if tools is iterable and tools | length > 0 %}\n {{- '<|im_start|><|system|>'}}\n {{- '당신은 도구 호출 기능을 갖춘 유용한 도우미입니다. 사용자의 요청을 처리하기 위해서 필요한 도구가 주어진 목록에 있는 경우 도구 호출로 응답하세요.\n필요한 도구가 목록에 없는 경우에는 도구 호출 없이 사용자가 요구한 정보를 제공하세요.\n필요한 도구가 목록에 있지만 해당 도구를 호출하는데 필요한 argument 정보가 부족한 경우 해당 정보를 사용자에게 요청하세요.\n사용자의 요청을 처리하기 위해 여러번 도구를 호출할 수 있어야 합니다.\n도구 호출 이후 도구 실행 결과를 입력으로 받으면 해당 결과를 활용하여 답변을 생성하세요.\n\n다음은 접근할 수 있는 도구들의 목록 입니다:\n<tools>\n'}}\n {%- for t in tools %}\n {{- t | tojson }}\n {{- '\n' }}\n {%- endfor %}\n {{- '</tools>' }}\n {{- '\n\n도구를 호출하려면 아래의 JSON으로 응답하세요.\n도구 호출 형식: <tool_call>{\"name\": 도구 이름, \"arguments\": dictionary 형태의 도구 인자값}</tool_call>' }}\n {{- '<|im_end|>' }}\n {%- endif %}\n \n {%- for message in messages %}\n {%- if message.role == 'system' %}\n {{- '<|im_start|><|system|>' + message.content + '<|im_end|>'}}\n {%- elif message.role == 'user' %}\n {{- '<|im_start|><|user|>' + message.content + '<|im_end|>'}}\n {%- elif message.role == 'assistant' %}\n {{- '<|im_start|><|assistant|>'}}\n {%- set content = '' %}\n {%- if message.content is defined %}\n {%- set content = message.content %}\n {%- endif %}\n \n {%- if add_generation_prompt and not (message.reasoning_content is defined and message.reasoning_content is not none) %}\n {%- if '</think>' in message.content %}\n {%- set content = message.content.split('</think>'.strip())[-1].lstrip('\\n') %}\n {%- endif %}\n {%- endif %}\n \n {{- content}}\n {%- if message.tool_calls is defined %}\n {%- for tool_call in message.tool_calls %}\n {%- if tool_call.function is defined %}\n {%- set tool_call = tool_call.function %}\n {%- endif %}\n {{- '<tool_call>' }}\n {{- '{' }}\n {{- '\"name\": \"' }}\n {{- tool_call.name }}\n {{- '\"' }}\n {%- if tool_call.arguments is defined %}\n {{- ', ' }}\n {{- '\"arguments\": ' }}\n {{- tool_call.arguments|tojson }}\n {%- endif %}\n {{- '}' }}\n {{- '</tool_call>' }}\n {%- endfor %}\n {%- endif %}\n {{- '<|im_end|>'}}\n \n {%- elif message.role == 'tool' %}\n {{- '<|im_start|><|extra_id_13|><tool_output>' + message.content + '</tool_output><|im_end|>'}}\n {%- endif %}\n {%- endfor %}\n \n {%- if add_generation_prompt %}\n {{- '<|im_start|><|assistant|>' }}\n {%- endif %}",
|
| 375 |
+
"clean_up_tokenization_spaces": true,
|
| 376 |
+
"cls_token": "<|cls|>",
|
| 377 |
+
"eod_token": "<|endoftext|>",
|
| 378 |
+
"eos_token": "<|im_end|>",
|
| 379 |
+
"errors": "replace",
|
| 380 |
+
"mask_token": "<|mask|>",
|
| 381 |
+
"max_length": 7680,
|
| 382 |
+
"model_max_length": 262144,
|
| 383 |
+
"pad_token": "<|pad|>",
|
| 384 |
+
"padding_side": "right",
|
| 385 |
+
"sep_token": "<|sep|>",
|
| 386 |
+
"tokenizer_class": "GPT2Tokenizer",
|
| 387 |
+
"truncation_side": "left",
|
| 388 |
+
"unk_token": "<|unk|>",
|
| 389 |
+
"vocab_size": 102400
|
| 390 |
+
}
|
| 391 |
+
|
vocab.json
ADDED
|
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See raw diff
|
|
|