onkolahmet/text_to_sql

1---2base_model: Qwen/Qwen2-0.5B-Instruct3library_name: transformers4model_name: tmp_trainer5tags:6- generated_from_trainer7- trl8- sft9licence: license10---11 12# Model Card for tmp_trainer13 14This model is a fine-tuned version of [Qwen/Qwen2-0.5B-Instruct](https://huggingface.co/Qwen/Qwen2-0.5B-Instruct).15It has been trained using [TRL](https://github.com/huggingface/trl).16 17## Quick start18 19```python20from transformers import pipeline21 22question = "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?"23generator = pipeline("text-generation", model="onkolahmet/tmp_trainer", device="cuda")24output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0]25print(output["generated_text"])26```27 28## Training procedure29 30 31 32This model was trained with SFT.33 34### Framework versions35 36- TRL: 0.12.237- Transformers: 4.46.338- Pytorch: 2.6.039- Datasets: 3.4.140- Tokenizers: 0.20.341 42## Citations43 44 45 46Cite TRL as:47    48```bibtex49@misc{vonwerra2022trl,50	title        = {{TRL: Transformer Reinforcement Learning}},51	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},52	year         = 2020,53	journal      = {GitHub repository},54	publisher    = {GitHub},55	howpublished = {\url{https://github.com/huggingface/trl}}56}57```