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aisingapore
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Model Details
Model Provider
aisingapore
Model Tree
Base
this model
Input Modalities
Text
Output Modalities
Text
Supported Functionality
Dedicated Endpoints
Container
python
from transformers import pipelinequestion = "If you had a time machine, but could only go to the past or the future once and never return, which would you choose and why?"generator = pipeline("text-generation", model="aisingapore/Qwen3-0.6B-Base-DuDi", device="cuda")output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0]print(output["generated_text"])
This model was trained with DuDi, a method introduced in DuDi: Dual-Signal Distillation with Cross-Lingual Verbalizer.
Cite DuDi as:
bibtex
@misc{payoungkhamdee2026dudidualsignaldistillationcrosslingual,title={DuDi: Dual-Signal Distillation with Cross-Lingual Verbalizer},author={Patomporn Payoungkhamdee and Tinnakit Udsa and Jian Gang Ngui and Sarana Nutanong and Alham Fikri Aji and Peerat Limkonchotiwat},year={2026},eprint={2606.04694},archivePrefix={arXiv},primaryClass={cs.CL},url={https://arxiv.org/abs/2606.04694},}
Cite TRL as:
bibtex
@software{vonwerra2020trl,title = {{TRL: Transformers Reinforcement Learning}},author = {von Werra, Leandro and Belkada, Younes and Tunstall, Lewis and Beeching, Edward and Thrush, Tristan and Lambert, Nathan and Huang, Shengyi and Rasul, Kashif and Gallouédec, Quentin},license = {Apache-2.0},url = {https://github.com/huggingface/trl},year = {2020}}