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engiopt-neurips-diffusion-2d-cond
IDEALLab/engiopt-neurips-diffusion-2d-cond
engiopt-neurips-diffusion-2d-cond is a machine learning model from IDEALLab. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
Checkpoints from EngiBench: A Framework for Data-Driven Engineering Design Research (NeurIPS 2025 Datasets & Benchmarks, arXiv:2508.00831), migrated off Weights & Biases.
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Updated Aug 7, 2026
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At a glance
- Access
- Public
- Created
- Aug 7, 2026
- Updated
- Aug 7, 2026
- SHA
- f038cb25
Model card
From the Hugging Face model README
Legacy NeurIPS 2025 checkpoints -- diffusion_2d_cond
Checkpoints from EngiBench: A Framework for Data-Driven Engineering Design Research (NeurIPS 2025 Datasets & Benchmarks, arXiv:2508.00831), migrated off Weights & Biases.
These are NOT comparable to current EngiOpt checkpoints. The EngiBench problem definitions have changed since the paper, so a result here and a result in
IDEALLab/engiopt-diffusion-2d-condfor the same problem id measure different things. They are kept under a separate repo prefix for exactly this reason. Use these only to reproduce the paper.
Layout: {problem_id}/{wandb_collection}/{version}/. See legacy_index.json for provenance (W&B run id, aliases, seed, timestamps).
- Created
- Aug 7, 2026
- Updated
- Aug 7, 2026