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--- |
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license: mit |
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language: |
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- en |
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pipeline_tag: visual-question-answering |
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library_name: transformers |
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base_model: |
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- OpenGVLab/InternVL2-2B |
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datasets: |
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- TIGER-Lab/Mantis-Instruct |
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--- |
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# 🐟 TAID-VLM-2B |
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🤗 [Models](https://huggingface.co/SakanaAI) | 📚 [Paper](https://arxiv.org/abs/2501.16937) | 📝 [Blog](https://sakana.ai/taid/) | 🐦 [Twitter](https://twitter.com/SakanaAILabs) |
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**TAID-VLM-2B** is a vision-language model created through TAID (Temporally Adaptive Interpolated Distillation), our new knowledge distillation method. |
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We used [InternVL2-8B](https://huggingface.co/OpenGVLab/InternVL2-8B) as the teacher model and [InternVL2-2B](https://huggingface.co/OpenGVLab/InternVL2-2B) as the student model. |
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## Model Details |
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- **Developed by:** [Sakana AI](https://sakana.ai/) |
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- **Model type:** Autoregressive Vision-Language Model |
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- **Language(s):** English |
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- **License:** [MIT License](./LICENSE) |
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- **Paper:** https://arxiv.org/abs/2501.16937 |
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- **Blog:** https://sakana.ai/taid/ |
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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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This model is based on results obtained from a project, JPNP20017, subsidized by the New Energy and Industrial Technology Development Organization (NEDO). |
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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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``` |
