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---
license: apache-2.0
language:
- ja
pipeline_tag: text-generation
library_name: transformers
base_model:
- Qwen/Qwen2.5-1.5B-Instruct
---
# TinySwallow-1.5B
🤗 [Models](https://huggingface.co/SakanaAI) | 📚 [Paper](https://arxiv.org/abs/2501.16937) | 📝 [Blog](https://sakana.ai/taid-jp/) | 🐦 [Twitter](https://twitter.com/SakanaAILabs)
**TinySwallow-1.5B** is a Japanese compact language model created through *TAID (Temporally Adaptive Interpolated Distillation)*, our new knowledge distillation method.
We used [Qwen2.5-32B-Instruct](https://huggingface.co/Qwen/Qwen2.5-32B-Instruct) as the teacher model and [Qwen2.5-1.5B-Instruct](https://huggingface.co/Qwen/Qwen2.5-1.5B-Instruct) as the student model.
The model has been further pre-trained on Japanese text data to enhance its Japanese language capabilities.
If you are looking for an instruction-following model, check [TinySwallow-1.5B-Instruct](https://huggingface.co/SakanaAI/TinySwallow-1.5B-Instruct).
## Model Details
- **Developed by:** [Sakana AI](https://sakana.ai/) and [Swallow Team](https://swallow-llm.github.io/index.en.html)
- **Model type:** Autoregressive Language Model
- **Language(s):** Japanese
- **License:** [Apache License, Version 2.0](./LICENSE)
- **Paper:** https://arxiv.org/abs/2501.16937
- **Blog:** https://sakana.ai/taid-jp/
## Uses
This model is provided for research and development purposes only and should be considered as an experimental prototype.
It is not intended for commercial use or deployment in mission-critical environments.
Use of this model is at the user's own risk, and its performance and outcomes are not guaranteed.
Sakana AI shall not be liable for any direct, indirect, special, incidental, or consequential damages, or any loss arising from the use of this model, regardless of the results obtained.
Users must fully understand the risks associated with the use of this model and use it at their own discretion.
## Acknowledgement
We would like to thank the developers of the source models for their contributions and for making their work available.
## Authors
* [Sakana AI](https://sakana.ai/)
* [Makoto Shing](https://huggingface.co/mkshing)
* [Taishi Nakamura](https://x.com/Setuna7777_2)
* [Kou Misaki](https://huggingface.co/takkyu2)
* [Takuya Akiba](https://huggingface.co/iwiwi)
* [Swallow Team](https://swallow-llm.github.io/index.en.html)
* [Naoki Okazaki](https://www.chokkan.org/index.ja.html)
* [Youmi Ma](https://www.nlp.c.titech.ac.jp/member/youmi.en.html)
* [Kakeru Hattori](https://aya-se.vercel.app/)
* [Kazuki Fujii](https://x.com/okoge_kaz)
* [Sakae Mizuki](https://s-mizuki-nlp.github.io/)
## Citation
```bibtex
@misc{sakana2025taid,
title = {TAID: Temporally Adaptive Interpolated Distillation for Efficient Knowledge Transfer in Language Models},
author. = {Makoto Shing and Kou Misaki and Han Bao and Sho Yokoi and Takuya Akiba},
year = {2025},
eprint = {2501.16937},
archivePrefix = {arXiv},
primaryClass = {cs.LG},
url = {https://arxiv.org/abs/2501.16937}
}
```

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"bos_token": null,
"chat_template": "{%- if tools %}\n {{- '<|im_start|>system\\n' }}\n {%- if messages[0]['role'] == 'system' %}\n {{- messages[0]['content'] }}\n {%- else %}\n {{- 'You are Qwen, created by Alibaba Cloud. You are a helpful assistant.' }}\n {%- endif %}\n {{- \"\\n\\n# Tools\\n\\nYou may call one or more functions to assist with the user query.\\n\\nYou are provided with function signatures within <tools></tools> XML tags:\\n<tools>\" }}\n {%- for tool in tools %}\n {{- \"\\n\" }}\n {{- tool | tojson }}\n {%- endfor %}\n {{- \"\\n</tools>\\n\\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\\n<tool_call>\\n{\\\"name\\\": <function-name>, \\\"arguments\\\": <args-json-object>}\\n</tool_call><|im_end|>\\n\" }}\n{%- else %}\n {%- if messages[0]['role'] == 'system' %}\n {{- '<|im_start|>system\\n' + messages[0]['content'] + '<|im_end|>\\n' }}\n {%- else %}\n {{- '<|im_start|>system\\nYou are Qwen, created by Alibaba Cloud. You are a helpful assistant.<|im_end|>\\n' }}\n {%- endif %}\n{%- endif %}\n{%- for message in messages %}\n {%- if (message.role == \"user\") or (message.role == \"system\" and not loop.first) or (message.role == \"assistant\" and not message.tool_calls) %}\n {{- '<|im_start|>' + message.role + '\\n' + message.content + '<|im_end|>' + '\\n' }}\n {%- elif message.role == \"assistant\" %}\n {{- '<|im_start|>' + message.role }}\n {%- if message.content %}\n {{- '\\n' + message.content }}\n {%- endif %}\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 {{- '\\n<tool_call>\\n{\"name\": \"' }}\n {{- tool_call.name }}\n {{- '\", \"arguments\": ' }}\n {{- tool_call.arguments | tojson }}\n {{- '}\\n</tool_call>' }}\n {%- endfor %}\n {{- '<|im_end|>\\n' }}\n {%- elif message.role == \"tool\" %}\n {%- if (loop.index0 == 0) or (messages[loop.index0 - 1].role != \"tool\") %}\n {{- '<|im_start|>user' }}\n {%- endif %}\n {{- '\\n<tool_response>\\n' }}\n {{- message.content }}\n {{- '\\n</tool_response>' }}\n {%- if loop.last or (messages[loop.index0 + 1].role != \"tool\") %}\n {{- '<|im_end|>\\n' }}\n {%- endif %}\n {%- endif %}\n{%- endfor %}\n{%- if add_generation_prompt %}\n {{- '<|im_start|>assistant\\n' }}\n{%- endif %}\n",
"clean_up_tokenization_spaces": false,
"eos_token": "<|im_end|>",
"errors": "replace",
"model_max_length": 131072,
"pad_token": "<|endoftext|>",
"split_special_tokens": false,
"tokenizer_class": "Qwen2Tokenizer",
"unk_token": null
}

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vocab.json Normal file
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