Typhoon T1: An Open Thai Reasoning Model
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arXiv
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| Autores principales: | , , , |
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| Formato: | Preprint |
| Publicado: |
2025
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| Acceso en línea: | |
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| _version_ | 1866910895968354304 |
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| author | Taveekitworachai, Pittawat Manakul, Potsawee Tharnpipitchai, Kasima Pipatanakul, Kunat |
| author_facet | Taveekitworachai, Pittawat Manakul, Potsawee Tharnpipitchai, Kasima Pipatanakul, Kunat |
| contents | This paper introduces Typhoon T1, an open effort to develop an open Thai reasoning model. A reasoning model is a relatively new type of generative model built on top of large language models (LLMs). A reasoning model generates a long chain of thought before arriving at a final answer, an approach found to improve performance on complex tasks. However, details on developing such a model are limited, especially for reasoning models that can generate traces in a low-resource language. Typhoon T1 presents an open effort that dives into the details of developing a reasoning model in a more cost-effective way by leveraging supervised fine-tuning using open datasets, instead of reinforcement learning. This paper shares the details about synthetic data generation and training, as well as our dataset and model weights. Additionally, we provide insights gained from developing a reasoning model that generalizes across domains and is capable of generating reasoning traces in a low-resource language, using Thai as an example. We hope this open effort provides a foundation for further research in this field. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2502_09042 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Typhoon T1: An Open Thai Reasoning Model Taveekitworachai, Pittawat Manakul, Potsawee Tharnpipitchai, Kasima Pipatanakul, Kunat Computation and Language Artificial Intelligence This paper introduces Typhoon T1, an open effort to develop an open Thai reasoning model. A reasoning model is a relatively new type of generative model built on top of large language models (LLMs). A reasoning model generates a long chain of thought before arriving at a final answer, an approach found to improve performance on complex tasks. However, details on developing such a model are limited, especially for reasoning models that can generate traces in a low-resource language. Typhoon T1 presents an open effort that dives into the details of developing a reasoning model in a more cost-effective way by leveraging supervised fine-tuning using open datasets, instead of reinforcement learning. This paper shares the details about synthetic data generation and training, as well as our dataset and model weights. Additionally, we provide insights gained from developing a reasoning model that generalizes across domains and is capable of generating reasoning traces in a low-resource language, using Thai as an example. We hope this open effort provides a foundation for further research in this field. |
| title | Typhoon T1: An Open Thai Reasoning Model |
| topic | Computation and Language Artificial Intelligence |
| url | https://arxiv.org/abs/2502.09042 |