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--- |
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library_name: granite_tsfm |
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base_model: ibm-granite/granite-timeseries-ttm-r2 |
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tags: |
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- ttm4hvac |
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- tsfm |
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- digital twin |
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- hvac |
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- energy |
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- experiment |
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license: apache-2.0 |
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papers: |
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- title: "Transfer learning of building dynamics digital twin for HVAC control with Time-series Foundation Model" |
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url: https://arxiv.org/abs/XXXX.XXXXX |
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authors: "Ferran Aran Domingo" |
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datasets: |
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- gft/ttm4hvac-source-default-train |
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- gft/ttm4hvac-target-heat-test |
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- gft/ttm4hvac-target-cool-test |
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pipeline_tag: time-series-forecasting |
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--- |
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# TTM4HVAC – TinyTimeMixer for HVAC dynamics modeling |
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This repository contains the **TTM4HVAC – source-default** fine-tuned TinyTimeMixer model. |
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It corresponds to the **“source-default” experiment** described in the TTM4HVAC paper, where the model is trained only on **default rule-based control (RBC)** trajectories across all simulated source buildings and climates. |
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This model is part of the TTM4HVAC family, but **is not the main recommended checkpoint**. |
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For full documentation, usage examples, and the best-performing model, please visit: |
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👉 **Main model card:** https://huggingface.co/gft/ttm4hvac |
