--- base_model: barc0/Llama-3.1-ARC-Potpourri-Induction-8B datasets: - suehyunpark/induction_arc_inputs_train_bc_trajectories_max10-per-task_warm-start library_name: transformers model_name: barc0/Llama-3.1-ARC-Potpourri-Induction-8B tags: - generated_from_trainer - alignment-handbook - trl - sft licence: license --- # Model Card for barc0/Llama-3.1-ARC-Potpourri-Induction-8B This model is a fine-tuned version of [barc0/Llama-3.1-ARC-Potpourri-Induction-8B](https://huggingface.co/barc0/Llama-3.1-ARC-Potpourri-Induction-8B) on the [['suehyunpark/induction_arc_inputs_train_bc_trajectories_max10-per-task_warm-start']](https://huggingface.co/datasets/['suehyunpark/induction_arc_inputs_train_bc_trajectories_max10-per-task_warm-start']) 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="suehyunpark/potpourri-8b-inst-fft-induction-bc-trajectory-max10-per-task-warm-start", 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/suehyun/arc-improve/runs/uuc18xow) This model was trained with SFT. ### Framework versions - TRL: 0.12.0 - Transformers: 4.46.2 - Pytorch: 2.5.1 - Datasets: 3.1.0 - Tokenizers: 0.20.3 ## 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}} } ```