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license: apache-2.0 |
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language: |
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- ja |
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# Leia-Swallow-7B |
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LEIA is a training technique for autoregressive LLMs that effectively improves their performance in languages other than English by enhancing cross-lingual knowledge transfer from English to a target language. |
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This model is constructed by applying LEIA to Swallow, a Japanese-English bilingual LLM based on LLaMA 2. |
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The model achieves enhanced performance on six Japanese question-answering benchmarks, as reported below. |
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Please refer to our paper or blog post (in Japanese) for further technical details. |
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- [LEIA: Facilitating Cross-Lingual Knowledge Transfer in Language Models with Entity-based Data Augmentation](https://arxiv.org/abs/2402.11485) (arxiv.org) |
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- [LEIA: 言語間転移学習でLLMを賢くする新しい方法](#) (zenn.dev) |
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## Model List |
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- [Leia-Swallow-7b](https://huggingface.co/leia-llm/Leia-Swallow-7b/) |
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- [Leia-Swallow-13b](https://huggingface.co/leia-llm/Leia-Swallow-13b/) |
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## Empirical Results |
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The model is assessed using the following six question answering benchmarks: |
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- X-CODAH |
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- X-CSQA |
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- JCommonsenseQA |
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- NIILC |
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- JEMHopQA |
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- JAQKET v2 |
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| Model | X-CODAH | X-CSQA | JCommonsenseQA | NIILC | JEMHopQA | JAQKET v2 | |
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| ---- | ---- | ---- | ---- | ---- | ---- | ---- | |
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| Swallow | 42.0 | 41.0 | 80.3 | 59.5 | 50.8 | 86.2 | |
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| LEIA | **42.7** | **42.4** | **80.6** | **60.3** | **54.7** | **86.5** | |
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For further details of this experiment, please refer to [our paper](https://arxiv.org/abs/2402.11485). |
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## Contributors |
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- Ikuya Yamada (Studio Ousia, RIKEN) |
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- Ryokan Ri (LY Corporation, SB Intuitions) |
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