--- base_model: Qwen/Qwen3-4B-Base datasets: CohenQu/HintGen-STaR.04.00 library_name: transformers model_name: Qwen3-4B-Base_HintGen-STaR.04.00_1e-6_no_think tags: - generated_from_trainer - trl - sft licence: license --- # Model Card for Qwen3-4B-Base_HintGen-STaR.04.00_1e-6_no_think This model is a fine-tuned version of [Qwen/Qwen3-4B-Base](https://huggingface.co/Qwen/Qwen3-4B-Base) on the [CohenQu/HintGen-STaR.04.00](https://huggingface.co/datasets/CohenQu/HintGen-STaR.04.00) dataset. It has been trained using [TRL](https://github.com/huggingface/trl). ## Quick start ```python from transformers import pipeline question = "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="CohenQu/Qwen3-4B-Base_HintGen-STaR.04.00_1e-6_no_think", device="cuda") output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0] print(output["generated_text"]) ``` ## Training procedure [Visualize in Weights & Biases](https://wandb.ai/yuxiao98/hint-generator/runs/wzd2ze1v) This model was trained with SFT. ### Framework versions - TRL: 0.17.0.dev0 - Transformers: 4.51.3 - Pytorch: 2.5.1 - Datasets: 3.5.0 - Tokenizers: 0.21.1 ## Citations Cite TRL as: ```bibtex @misc{vonwerra2022trl, title = {{TRL: Transformer Reinforcement Learning}}, author = {Leandro von Werra and Younes Belkada and Lewis Tunstall and Edward Beeching and Tristan Thrush and Nathan Lambert and Shengyi Huang and Kashif Rasul and Quentin Gallouédec}, year = 2020, journal = {GitHub repository}, publisher = {GitHub}, howpublished = {\url{https://github.com/huggingface/trl}} } ```