| | --- |
| | library_name: granite_tsfm |
| | base_model: ibm-granite/granite-timeseries-ttm-r2 |
| | tags: |
| | - ttm4hvac |
| | - tsfm |
| | - digital twin |
| | - hvac |
| | - energy |
| | - experiment |
| | license: apache-2.0 |
| | datasets: |
| | - gft/ttm4hvac-target-default-train |
| | - gft/ttm4hvac-target-heat-test |
| | - gft/ttm4hvac-target-cool-test |
| | pipeline_tag: time-series-forecasting |
| | papers: |
| | - title: "Transfer learning of building dynamics digital twin for HVAC control with Time-series Foundation Model" |
| | url: https://arxiv.org/abs/XXXX.XXXXX |
| | authors: "Ferran Aran Domingo" |
| | --- |
| | |
| | # TTM4HVAC – TinyTimeMixer for HVAC dynamics modeling |
| |
|
| | This repository contains the **TTM4HVAC – target-default** fine-tuned TinyTimeMixer model. |
| |
|
| | It corresponds to the **“target-default” experiment** from the TTM4HVAC paper, where the model is fine-tuned solely on **default RBC data from the target building** (BestestAir, Denver climate). |
| |
|
| | This checkpoint is part of the TTM4HVAC experiment family. |
| | For the main model, recommended usage, detailed examples, and full documentation, please see: |
| |
|
| | 👉 **Main model card:** https://huggingface.co/gft/ttm4hvac |
