--- {{ card_data }} --- # Model Card for {{ model_name }} This model is a fine-tuned version of [{{ base_model }}](https://huggingface.co/{{ base_model }}){% if dataset_name %} on the [{{ dataset_name }}](https://huggingface.co/datasets/{{ dataset_name }}) dataset{% endif %}. 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="{{ hub_model_id }}", device="cuda") output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0] print(output["generated_text"]) ``` ## Training procedure {% if wandb_url %}[Visualize in Weights & Biases]({{ wandb_url }}){% endif %} {% if comet_url %}[Visualize in Comet]({{ comet_url }}){% endif %} This model was trained with {{ trainer_name }}{% if paper_id %}, a method introduced in [{{ paper_title }}](https://huggingface.co/papers/{{ paper_id }}){% endif %}. ### Framework versions - TRL: {{ trl_version }} - Transformers: {{ transformers_version }} - Pytorch: {{ pytorch_version }} - Datasets: {{ datasets_version }} - Tokenizers: {{ tokenizers_version }} ## Citations {% if trainer_citation %}Cite {{ trainer_name }} as: ```bibtex {{ trainer_citation }} ```{% endif %} Cite TRL as: ```bibtex {% raw %}@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 Gallou{\'e}dec}, year = 2020, journal = {GitHub repository}, publisher = {GitHub}, howpublished = {\url{https://github.com/huggingface/trl}} }{% endraw %} ```