Instructions to use allenai/ACE2S-SHiELD-plus-supplemental-checkpoints with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Full Model Emulation
How to use allenai/ACE2S-SHiELD-plus-supplemental-checkpoints with Full Model Emulation:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
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ACE2S-SHiELD+ supplemental checkpoints
This repository contains a collection of checkpoints associated with supplemental models trained and referenced in the ACE2S-SHiELD+ manuscript. These checkpoints may be useful for certain research purposes, but for almost all cases we recommend using the ACE2S-SHiELD+ checkpoint from this repository, which contains the model featured in the manuscript, which will likely produce the best results.
The models here were trained for ablation experiments and/or with alternative random seeds. The ablation experiments aimed to separate the impacts of including random CO2 data in training and imposing energy conservation. Accordingly models with four different configurations are included in separate subdirectories, which are described in the table below. For the technical details regarding what these different configuration options mean, please see discussion in the manuscript.
| Subdirectory | Description | Best inference seed |
|---|---|---|
ace2s_shield_plus_no_RC_no_EC |
Without random CO2 data or energy conservation | rs0_ckpt.tar |
ace2s_shield_plus_no_RC |
Without random CO2 data with energy conservation | rs0_ckpt.tar |
ace2s_shield_plus_no_EC |
With random CO2 data without energy conservation | rs1_ckpt.tar |
ace2s_shield_plus |
With random CO2 data and energy conservation | rs0_ckpt.tar* |
Two models with different random seeds were trained for each configuration.
Within each subdirectory they are labeled rs0_ckpt.tar and rs1_ckpt.tar. For
each model, the checkpoint was chosen from the epoch with best inline inference
skill. In the manuscript, unless results from both seeds are shown, for visual
clarity results from the model with best inline inference skill for the
particular configuration are used, which is denoted in the table above. In all
cases, inline inference consisted of an ensemble of simulations in 1x,
2x, and 4xCO2 equilibrium climates, and the error was computed based
on the approach described in
Watt-Meyer et al. (2025).
*This is the checkpoint featured in the main ACE2S-SHiELD-plus repository. Therefore it is not included in this repository.
License
These models are licensed under Apache 2.0. They are intended for research and educational use in accordance with Ai2’s Responsible Use Guidelines.
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