SoundsFun/peft-html_css_test_2

1---2base_model: open-r1/OlympicCoder-7B3library_name: transformers4model_name: peft-html_css_test_25tags:6- generated_from_trainer7- trl8- sft9licence: license10---11 12# Model Card for peft-html_css_test_213 14This model is a fine-tuned version of [open-r1/OlympicCoder-7B](https://huggingface.co/open-r1/OlympicCoder-7B).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="SoundsFun/peft-html_css_test_2", 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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="150" height="24"/>](https://wandb.ai/pasechnikm-mephi/huggingface/runs/iyuzl4ty)31 32This model was trained with SFT.33 34### Framework versions35 36- TRL: 0.12.037- Transformers: 4.51.0.dev038- Pytorch: 2.5.139- Datasets: 3.4.040- Tokenizers: 0.21.041 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 GallouГ©dec},52	year         = 2020,53	journal      = {GitHub repository},54	publisher    = {GitHub},55	howpublished = {\url{https://github.com/huggingface/trl}}56}57```