EXAONE 3.5: Series of Large Language Models for Real-world Use Cases
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| Formato: | Preprint |
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2024
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| _version_ | 1866915702208724992 |
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| author | An, Soyoung Bae, Kyunghoon Choi, Eunbi Choi, Kibong Choi, Stanley Jungkyu Hong, Seokhee Hwang, Junwon Jeon, Hyojin Jo, Gerrard Jeongwon Jo, Hyunjik Jung, Jiyeon Jung, Yountae Kim, Hyosang Kim, Joonkee Kim, Seonghwan Kim, Soyeon Kim, Sunkyoung Kim, Yireun Kim, Yongil Kim, Youchul Lee, Edward Hwayoung Lee, Haeju Lee, Honglak Lee, Jinsik Lee, Kyungmin Lim, Woohyung Park, Sangha Park, Sooyoun Park, Yongmin Yang, Sihoon Yeen, Heuiyeen Yun, Hyeongu |
| author_facet | An, Soyoung Bae, Kyunghoon Choi, Eunbi Choi, Kibong Choi, Stanley Jungkyu Hong, Seokhee Hwang, Junwon Jeon, Hyojin Jo, Gerrard Jeongwon Jo, Hyunjik Jung, Jiyeon Jung, Yountae Kim, Hyosang Kim, Joonkee Kim, Seonghwan Kim, Soyeon Kim, Sunkyoung Kim, Yireun Kim, Yongil Kim, Youchul Lee, Edward Hwayoung Lee, Haeju Lee, Honglak Lee, Jinsik Lee, Kyungmin Lim, Woohyung Park, Sangha Park, Sooyoun Park, Yongmin Yang, Sihoon Yeen, Heuiyeen Yun, Hyeongu |
| contents | This technical report introduces the EXAONE 3.5 instruction-tuned language models, developed and released by LG AI Research. The EXAONE 3.5 language models are offered in three configurations: 32B, 7.8B, and 2.4B. These models feature several standout capabilities: 1) exceptional instruction following capabilities in real-world scenarios, achieving the highest scores across seven benchmarks, 2) outstanding long-context comprehension, attaining the top performance in four benchmarks, and 3) competitive results compared to state-of-the-art open models of similar sizes across nine general benchmarks. The EXAONE 3.5 language models are open to anyone for research purposes and can be downloaded from https://huggingface.co/LGAI-EXAONE. For commercial use, please reach out to the official contact point of LG AI Research: contact_us@lgresearch.ai. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2412_04862 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | EXAONE 3.5: Series of Large Language Models for Real-world Use Cases An, Soyoung Bae, Kyunghoon Choi, Eunbi Choi, Kibong Choi, Stanley Jungkyu Hong, Seokhee Hwang, Junwon Jeon, Hyojin Jo, Gerrard Jeongwon Jo, Hyunjik Jung, Jiyeon Jung, Yountae Kim, Hyosang Kim, Joonkee Kim, Seonghwan Kim, Soyeon Kim, Sunkyoung Kim, Yireun Kim, Yongil Kim, Youchul Lee, Edward Hwayoung Lee, Haeju Lee, Honglak Lee, Jinsik Lee, Kyungmin Lim, Woohyung Park, Sangha Park, Sooyoun Park, Yongmin Yang, Sihoon Yeen, Heuiyeen Yun, Hyeongu Computation and Language This technical report introduces the EXAONE 3.5 instruction-tuned language models, developed and released by LG AI Research. The EXAONE 3.5 language models are offered in three configurations: 32B, 7.8B, and 2.4B. These models feature several standout capabilities: 1) exceptional instruction following capabilities in real-world scenarios, achieving the highest scores across seven benchmarks, 2) outstanding long-context comprehension, attaining the top performance in four benchmarks, and 3) competitive results compared to state-of-the-art open models of similar sizes across nine general benchmarks. The EXAONE 3.5 language models are open to anyone for research purposes and can be downloaded from https://huggingface.co/LGAI-EXAONE. For commercial use, please reach out to the official contact point of LG AI Research: contact_us@lgresearch.ai. |
| title | EXAONE 3.5: Series of Large Language Models for Real-world Use Cases |
| topic | Computation and Language |
| url | https://arxiv.org/abs/2412.04862 |