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Check out the documentation for more information.
Thoughtful Thermostat
These are the weights in gguf format for the "thoughtful thermostat" from our paper Teaching Things To Think: Bootstrapping Local Reasoning for Smart(er) Devices.
The base model has been fine-tuned to take "action" and "explanation" oriented commands that a user might give to a smart thermostat and generate either JSON actions or natural language explanations in response.
Please refer to the GitHub repo for more information.
Prompt Structure
The models are fine-tuned to accept prompts in this format:
Action
User: {command}
[SENSORS] {sensor json} [/SENSORS]
Output: [SETTINGS]
Introspection
User: {command}
[SENSORS] {sensor json} [/SENSORS]
[SETTINGS] {settings json} [/SETTINGS]
Output: [EXPLANATION]
Citation
If our work is helpful, please cite us:
@inproceedings{king2025teaching,
title={Teaching Things To Think: Bootstrapping Local Reasoning for Smart (er) Devices},
author={King, Evan and Yu, Haoxiang and Vartak, Sahil and Jacob, Jenna and Lee, Sangsu and Julien, Christine},
booktitle={2025 IEEE International Conference on Pervasive Computing and Communications (PerCom)},
pages={78--88},
year={2025},
organization={IEEE}
}
Contact
Contact Evan King with questions, or open an issue on the repository.
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