This model is a fine-tuned version of google/functiongemma-270m-it. It has been trained using TRL. Quick start
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3 excerptsbasemodel: google/functiongemma-270m-it libraryname: transformers modelname: mobile-actions-functiongemma tags: generatedfromtrainer trl sft licence: license
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"]) 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}} } This model is a fine-tuned version of google/functiongemma-270m-it. It has been trained using TRL. Quick start
nitinr910/mobile-actions-functiongemma