Mobile Actions Functiongemma

--- base_model: google/functiongemma-270m-it library_name: transformers model_name: mobile-actions-functiongemma tags: - generated_from_trainer - trl - sft licence: license --- # Model Card for mobile-actions-functiongemma This model is a fine-tuned version of [google/functiongemma-270m-it](https://huggingface.co/google/functiongemma-270m-it). 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="nitinr910/mobile-actions-functiongemma", device="cuda") output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0] print(output["generated_text"]) ``` ## Training procedure This model was trained with SFT. ### Framework versions - TRL: 0.25.1 - Transformers: 4.57.1 - Pytorch: 2.11.0+cu128 - Datasets: 4.4.1 - Tokenizers: 0.22.2 ## 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 Gallou{\'e}dec}, year = 2020, journal = {GitHub repository}, publisher = {GitHub}, howpublished = {\url{https://github.com/huggingface/trl}} } ```

Source context: 20 downloads · 0 likes · Pipeline text-generation · Library transformers · Repo nitinr910/mobile-actions-functiongemma

Source context: 12 downloads · 0 likes · Pipeline text-generation · Library transformers · Repo nitinr910/mobile-actions-functiongemma