Synthetic Architectural Design Data for Language-Driven Generation

Aggregating synthetically generated data used to train the Architext models for language-driven generative architecture design. The data was created using a parametric design script in Grasshopper 3D. The dataset is categorized for text generation tasks and was last updated in May 2023.

Use Cases

• Train a text generation model on synthetically generated architectural design descriptions.
• Fine-tune a language model for architectural design tasks using the data referenced in the Architext paper.
• Analyze patterns in parametric design outputs generated by Grasshopper 3D scripts.

Strengths

• Data is associated with a published research paper (arXiv:2303.07519).
• Dataset is categorized for text generation tasks.
• Dataset was updated in May 2023.

Limitations

• The number of rows, columns, and sample data are unknown.
• The data is synthetically generated, which may not reflect real-world architectural constraints or distributions.
• Specific file formats and data structure details are unavailable.

Provenance

Source

Synthetically generated by a parametric design script in Grasshopper 3D.

Collection Method

Synthetic generation for model training, as described in the associated paper.

Freshness

Last updated on 2023-05-21.