--- base_model: Qwen/Qwen3-VL-32B-Instruct library_name: transformers model_name: qwen4-pointing tags: - generated_from_trainer - trackio:https://sano90-trackio.hf.space?project=huggingface&runs=sano90-1778491779&sidebar=collapsed - trl - sft licence: license --- # Model Card for qwen4-pointing This model is a fine-tuned version of [Qwen/Qwen3-VL-32B-Instruct](https://huggingface.co/Qwen/Qwen3-VL-32B-Instruct). 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="sano90/qwen4-pointing", device="cuda") output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0] print(output["generated_text"]) ``` ## Training procedure [ ](https://sano90-trackio.hf.space?project=huggingface&runs=sano90-1778491779&sidebar=collapsed) This model was trained with SFT. ### Framework versions - TRL: 1.0.0.dev0 - Transformers: 5.3.0 - Pytorch: 2.10.0 - Datasets: 4.8.3 - Tokenizers: 0.22.2 ## Citations 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} } ```
