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--- |
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license: apache-2.0 |
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language: |
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- ja |
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pipeline_tag: text-generation |
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library_name: transformers |
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base_model: |
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- Qwen/Qwen2.5-1.5B-Instruct |
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datasets: |
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- tokyotech-llm/lmsys-chat-1m-synth |
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- tokyotech-llm/swallow-magpie-ultra-v0.1 |
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- tokyotech-llm/swallow-swallow-gemma-magpie-v0.1 |
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--- |
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# TinySwallow-1.5B-Instruct |
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🤗 [Models](https://huggingface.co/SakanaAI) | 📚 [Paper](https://arxiv.org/abs/2501.16937) | 📝 [Blog](https://sakana.ai/taid-jp/) | 🐦 [Twitter](https://twitter.com/SakanaAILabs) |
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**TinySwallow-1.5B-Instruct** is an instruction-tuned version of [TinySwallow-1.5B](https://huggingface.co/SakanaAI/TinySwallow-1.5B), created through *TAID (Temporally Adaptive Interpolated Distillation)*, our new knowledge distillation method. |
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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. |
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The model has been further instruction-tuned to enhance its ability to follow instructions and engage in conversations in Japanese. |
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## Usage |
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Use the code below to get started with the model. |
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<details> |
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<summary> Click to expand </summary> |
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```python |
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import torch |
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from transformers import AutoModelForCausalLM, AutoTokenizer |
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# 1. load model |
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device = "cuda" if torch.cuda.is_available() else "cpu" |
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repo_id = "SakanaAI/TinySwallow-1.5B-Instruct" |
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model = AutoModelForCausalLM.from_pretrained(repo_id) |
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tokenizer = AutoTokenizer.from_pretrained(repo_id) |
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model.to(device) |
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# 2. prepare inputs |
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text = "知識蒸留について簡単に教えてください。" |
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messages = [{"role": "user", "content": text}] |
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input_ids = tokenizer.apply_chat_template(messages, add_generation_prompt=True, return_tensors="pt") |
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# 3. generate |
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output_ids = model.generate( |
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input_ids.to(device), |
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max_new_tokens=1024, |
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) |
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output_ids = output_ids[:, input_ids.shape[1] :] |
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generated_text = tokenizer.batch_decode(output_ids, skip_special_tokens=True)[0] |
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print(generated_text) |
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``` |
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</details> |
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## Model Details |
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- **Model type:** Autoregressive Language Model |
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- **Language(s):** Japanese |
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- **Paper:** https://arxiv.org/abs/2501.16937 |
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- **Blog:** https://sakana.ai/taid-jp/ |
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- **Training Datasets:** |
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- [Gemma-2-LMSYS-Chat-1M-Synth](https://huggingface.co/datasets/tokyotech-llm/lmsys-chat-1m-synth/blob/main/README_gemma.md) |
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- [tokyotech-llm/swallow-magpie-ultra-v0.1](https://huggingface.co/datasets/tokyotech-llm/swallow-magpie-ultra-v0.1) |
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- [tokyotech-llm/swallow-gemma-magpie-v0.1](https://huggingface.co/datasets/tokyotech-llm/swallow-gemma-magpie-v0.1) |
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## Uses |
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This model is provided for research and development purposes only and should be considered as an experimental prototype. |
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It is not intended for commercial use or deployment in mission-critical environments. |
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Use of this model is at the user's own risk, and its performance and outcomes are not guaranteed. |
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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. |
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Users must fully understand the risks associated with the use of this model and use it at their own discretion. |
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## Acknowledgement |
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We would like to thank the developers of the source models for their contributions and for making their work available. |
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## Authors |
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* [Sakana AI](https://sakana.ai/) |
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* [Makoto Shing](https://huggingface.co/mkshing) |
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* [Taishi Nakamura](https://x.com/Setuna7777_2) |
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* [Kou Misaki](https://huggingface.co/takkyu2) |
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* [Takuya Akiba](https://huggingface.co/iwiwi) |
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* [Swallow Team](https://swallow-llm.github.io/index.en.html) |
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* [Naoki Okazaki](https://www.chokkan.org/index.ja.html) |
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* [Youmi Ma](https://www.nlp.c.titech.ac.jp/member/youmi.en.html) |
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* [Kakeru Hattori](https://aya-se.vercel.app/) |
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* [Kazuki Fujii](https://x.com/okoge_kaz) |
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* [Sakae Mizuki](https://s-mizuki-nlp.github.io/) |
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## License |
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This model is derived from Qwen ([Apache 2.0](https://www.apache.org/licenses/LICENSE-2.0)) and trained on Gemma data ([Gemma Terms](https://ai.google.dev/gemma/terms), [Prohibited Use](https://ai.google.dev/gemma/prohibited_use_policy)). Use (including commercial) is permitted if you comply with both licenses/policies above. |
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## Citation |
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```bibtex |
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@misc{sakana2025taid, |
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title = {TAID: Temporally Adaptive Interpolated Distillation for Efficient Knowledge Transfer in Language Models}, |
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author. = {Makoto Shing and Kou Misaki and Han Bao and Sho Yokoi and Takuya Akiba}, |
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year = {2025}, |
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eprint = {2501.16937}, |
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archivePrefix = {arXiv}, |
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primaryClass = {cs.LG}, |
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url = {https://arxiv.org/abs/2501.16937} |
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} |
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``` |
