--- base_model: Qwen/Qwen2.5-7B-Instruct datasets: AlekseyKorshuk/ai-detection-gutenberg-human-choosed-formatted-ai-sft library_name: transformers model_name: ai-detection-gutenberg-human-choosed-formatted-ai-sft-qwen-7b-sft-3epochs tags: - generated_from_trainer - trl - sft licence: license --- # Model Card for ai-detection-gutenberg-human-choosed-formatted-ai-sft-qwen-7b-sft-3epochs This model is a fine-tuned version of [Qwen/Qwen2.5-7B-Instruct](https://huggingface.co/Qwen/Qwen2.5-7B-Instruct) on the [AlekseyKorshuk/ai-detection-gutenberg-human-choosed-formatted-ai-sft](https://huggingface.co/datasets/AlekseyKorshuk/ai-detection-gutenberg-human-choosed-formatted-ai-sft) 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="AlekseyKorshuk/ai-detection-gutenberg-human-choosed-formatted-ai-sft-qwen-7b-sft-3epochs", 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/aleksey-korshuk/huggingface/runs/wj4ikxoy) This model was trained with SFT. ### Framework versions - TRL: 0.12.0.dev0 - Transformers: 4.46.0 - Pytorch: 2.4.1+cu124 - Datasets: 3.0.1 - Tokenizers: 0.20.1 ## 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}} } ```